Disclosed are arrays for monitoring ecosystems, such as bodies of water, and methods and systems for making such arrays. In one embodiment, the array may include a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array is an oligonucleotide having a sequence derived from a single, predetermined operational taxonomic unit (OTU). The sequences immobilized on the array may be from known, or unknown organisms. Also disclosed are methods for identifying and isolating bioindicators diagnostic of specific ecosystems. The arrays and bioindicators of the invention may be used for rapid, and continual monitoring of ecosystems.
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13. A method for analyzing a pattern to evaluate the status of an ecosystem of interest comprising:
measuring hybridization of a nucleic acid sample isolated from the ecosystem of interest to an array of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU), and wherein the array comprises at least one oligonucleotide having the sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100, or SEQ ID NO: 106, or the complement of the sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100, or SEQ ID NO: 106; and
correlating a pattern of hybridization of the nucleic acid sample to the array with at least one parameter that comprises at least part of the ecosystem of interest.
1. A method for monitoring an ecosystem of interest comprising:
(a) generating an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, wherein each location on the substrate comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU), and wherein the array comprises at least one oligonucleotide having the sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, or SEQ ID NO: 100, or SEQ ID NO: 106, the complement of the sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106;
(b) preparing a nucleic acid sample from the ecosystem of interest;
(c) hybridizing the nucleic acid sample to the array;
(d) measuring hybridization of the nucleic acid sample to the array; and
(e) correlating hybridization of the nucleic acid sample to the array with at least one parameter that comprises at least part of the ecosystem of interest.
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This application is a continuation-in-part of U.S. patent application Ser. No. 10/131,618, filed Apr. 24, 2002 now abandoned. The disclosure of U.S. patent application Ser. No. 10/131,618, is hereby incorporated by reference in its entirety.
Parts of this work were supported by federal funding in the form of a Cooperative Agreement #82946501 with the Environmental Protection Agency to C. Neal Stewart, Vincent C. Henrich and Parke A. Rublee and an Environmental Protection Agency STAR Grant #R831627 to Parke A. Rublee.
The present invention relates to nucleic acid arrays to monitor water and other ecosystems.
As the threat of bioterrorist activities has become evident in recent years, concern about the vulnerability of ecosystems such as municipal water supplies to deliberate contamination has grown. Additionally, human development can result in chemicals, waste, and/or agricultural runoff being introduced into the ecosystem. Increases in population may lead to over-harvesting of marine resources, landscape alterations that alter the ecosystem, and the introduction of living and non-living contaminants into the ecosystem (Mallin, J. M., et al. 2000, Marine Pollution Bulletin, 41:56–75). For example, spills from concentrated animal feeding operations can degrade water quality and stimulate algal blooms (Mallin, M. A., 2000, American Scientist, 88:26–37). Also, over-development of coastal areas may introduce coliform bacteria, and the introduction of nutrients and or chemical compounds may lead to eutrophication or other changes in microbial communities (Mallin, M. A., et al. 2000, Ecological Applications, 10:1047–1056; Paerl, H. W., et al. 2003, FEMS Microbiology Ecology, 46:233–246; DeLorenzo, M. E., et al., 1999, Environmental Toxicology and Chemistry, 18:2824–2835).
Reservoirs, recreational lakes, and coastal areas can be difficult to secure against accidental or intentional contamination. Further, the contamination of a water source has the propensity to impact a relatively large population, and water filtration systems may not sufficiently alleviate the threat. Perhaps most troubling is the lack of a real-time test to detect the agents that are most likely to contaminate water supplies. The turnaround times for culturing microbes is slow enough that consumption of contaminated water may occur before the test results are known. Also, the expense involved in frequent monitoring of the water supply with currently available laboratory tests can be prohibitive.
As yet, there has not been a large-scale, deliberate contamination of a municipal water source. However, sporadic and relatively confined natural contaminations have demonstrated the importance in being able to monitor the water supply. The number of outbreaks attributable to contaminated drinking water supplies more than doubled in 1999–2000 over the previous two-year period, with contamination of well water also on the rise. In addition, recreational water sources have also reported significant increases in contamination (Bowman, 2002, Outbreaks of waterborne illnesses on the rise in US, Scripps-Howard News Service, Nov. 23, 2002). These incidents of water contamination were exacerbated by the difficulty in pinpointing the cause of the outbreak and subsequent misdiagnosis of the symptoms, illustrating the importance of “early warning” diagnostics of water supplies.
A number of microbial genome sequencing projects have been initiated to characterize pathogenic organisms. Although identification and characterization of genomic sequence data for individual pathogens may provide for the identification of specific microbes, such targeted testing fails to provide a comprehensive, economically feasible system for monitoring ecosystems of interest, such as municipal water supplies. The accuracy of a molecular diagnostic test for a microbe may be compromised where the pathogenic agent is endemic, or possesses substantial genetic similarity to non-pathogenic organisms (Leff et al., 1995, Appl. Environ. Microbiol., 61:1634–1636; Xiao et al, 1999, Appl Environ. Microbiol., 65:3386–3391). Also, although some putative contaminants of water have been identified, anticipating all possible contaminants is not feasible, and thus, specific tests are inherently limited.
Thus, there is a need for devices and methods that enable real-time monitoring of water supplies and other ecosystems of interest. The monitoring system should allow for detection of known, as well as unknown, contaminants. The monitoring system should be available in a format that is accessible for routine monitoring, as well as for rapid testing in response to a specific event.
The present invention provides devices and systems for monitoring water and other ecosystems. The present invention may be embodied in a variety of ways.
One embodiment of the present invention comprises an array for monitoring an ecosystem comprising a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU).
In another embodiment, the present invention may comprise a device for monitoring water quality comprising an array, wherein the array comprises a plurality of oligonucleotides immobilized at known locations on a substrate, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU).
Another embodiment of the present invention comprises a system for monitoring an ecosystem of interest. The system may comprise an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate. In one embodiment, the array may be designed such that each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU). The system may further include a device able to measure hybridization of a DNA sample to the array. Also, the system may include a DNA sample for hybridizing to the array. In one embodiment, the ecosystem may comprise a body of water.
Yet other embodiments of the present invention comprise methods for monitoring ecosystems. The method may comprise the step of generating an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence derived from a single predetermined microbial operational taxonomic unit (OTU). The method may also comprise the step of preparing a nucleic acid sample derived from a water sample of interest and hybridizing the nucleic acid sample to the array. Also, the method may comprise the step of measuring hybridization of the nucleic acid sample to the array, and correlating the hybridization of the nucleic acid to the array with a parameter that comprises at least part of the ecosystem. In one embodiment, the ecosystem of interest comprises a body of water.
In yet another embodiment, the present invention comprises a method of analyzing a pattern to evaluate the status of a biosystem. The method may comprise the step of measuring hybridization of a DNA sample to an array of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU), and correlating the hybridization of the DNA to the array with a parameter that comprises at least part of the ecosystem. A single change in the pattern of hybridization to the array for a first DNA sample isolated from an ecosystem of interest as compared to a second DNA sample isolated from an ecosystem of interest may be associated with a change in one parameter, or a plurality of parameters. Additionally or alternatively, a plurality of changes in the pattern of hybridization to the array for a first DNA sample isolated from an ecosystem of interest as compared to a second DNA sample isolated from an ecosystem of interest is associated with a change in one or more parameters. Samples may vary by location of the ecosystem, the time of sampling of a single ecosystem, or the location of sampling within a single ecosystem.
Embodiments of the present invention also comprise methods for identifying and/or generating bioindicators for ecosystems of interest. In one embodiment, a method of generating a bioindicator may comprise preparing a nucleic acid sample comprising a plurality of DNA molecules from an ecosystem of interest. The method may also comprise determining the sequence of at least some of the plurality of DNA molecules in the isolated DNA sample. The method may further comprise grouping the DNA sequences into operational taxonomic units (OTUs). Also, the method may comprise identifying at least one nucleic acid sequence that is specific to a single OTU. In one embodiment, the ecosystem of interest comprises a body of water.
Embodiments of the present invention also comprise bioindicators isolated using the methods and systems of the present invention. In one embodiment, the present invention comprises a bioindicator, or a collection of bioindicators, for the analysis of an ecosystem of interest, wherein a bioindicator comprises an isolated nucleic acid having a sequence derived from a single predetermined microbial operational taxonomic unit.
In yet another embodiment, the present invention also comprises a method to prepare a nucleic acid sample from a biosystem of interest, the nucleic acid sample comprising a plurality of bioindicator DNA sequences, comprising the step of amplifying a DNA sample isolated from a biosystem with a plurality of primers that have the ability to specifically amplify nucleic acid sequences comprising bioindicators. Also, in an embodiment, the present invention comprises an oligonucleotide primer having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof.
In yet another embodiment, the present invention may comprise a method to identify a microbe comprising the ability to modify, or adjust to, an ecosystem. The method may comprise the step of identifying a bioindicator that is associated with a particular microbe. Also, the method may comprise the steps of identifying the bioindicator in at least one ecosystem, and correlating the presence of the microbe with a parameter specific to the ecosystem. Also, the method may comprise identifying the nature of the ability of the microbe to modify, or adjust to, the ecosystem.
There may be certain advantages that may be realized with various embodiments of the present invention. By using a microarray comprising nucleic acid sequences that are specific to microbial operational taxonomic units, the array may cover a wide variety of microbial taxa. Thus, the array may provide a single test that provides substantially comprehensive information on community structure.
The array may, in certain embodiments, provide quantitative data. For example, by using quantifiable labels to label individual samples, or to differentially label specific sequences in a single sample, the array may provide information on the abundance of specific organisms of interest, such as key bioindicators, pathogens, or microbial contaminants in a water system.
Also, the array, if applied to a number of samples over time, may be able to indicate the “trajectory” of the system as either improving or degrading, where probes associated with the quality of the ecosystem of interest are known.
Microorganisms generally respond rapidly to environmental changes. The microarrays of the present invention may therefore provide results in near “real-time” (i.e., within hours) of an event, such as a contamination, occurring. Thus, the array may detect changes in ecosystem perturbations early, so that potential problems may be quickly rectified.
There may be a large number of microorganisms specific to any one ecosystem of interest, such as a specific body of water. Also, the prevalence of particular microorganisms may vary depending upon the water source. Still, by prudent selection of the nucleic acid sequences used as part of an array, the array may be diagnostic of a plurality of microorganisms that are specific to many types of ecosystems. Thus, once developed, the array can be a highly cost-effective way to monitor a variety of ecosystems. Also, the microarray platform may be easily modified and expanded to include new targets of interest as they are identified.
A microbial community may be affected by biological changes, physical changes, or chemical changes to the environment. Because the microarrays of the present invention provide a measure of the microbial community, the array may be sensitive to a wide variety of changes that may occur in the ecosystem of interest.
The present invention may be better understood by reference to the description and figures that follow. It is to be understood that the invention is not limited in its application to the specific details as set forth in the following description and figures. The invention is capable of other embodiments and of being practiced or carried out in various ways.
The present invention may be better understood by reference to the following figures. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
Ecogenomics is the recovery, characterization, and analysis of genomes recovered from organisms living in the natural environment. The present invention utilizes ecogenomics to develop nucleic acid based arrays for monitoring water supplies and other ecosystems.
Thus, the present invention provides methods, systems, and devices to monitor ecosystems. The methods, systems, and devices of the present invention may be used to monitor water. Embodiments of the present invention comprise bioindicators, and methods for isolating a bioindicator for the analysis of an ecosystem of interest. In one embodiment, the present invention comprises a method for developing bioindicators for monitoring water. The bioindicator may comprise a biological system, such as a microorganism, or a molecule, such as a nucleic acid sequence, that changes in response to a parameter that is related to the ecosystem of interest. The bioindicators may comprise known microorganisms or unknown microorganisms. Rather than measuring the microorganism itself, the present invention provides molecular bioindicators to monitor ecosystems of interest.
A bioindicator for the analysis of an ecosystem of interest may comprise an isolated nucleic acid having a sequence derived from a single predetermined microbial operational taxonomic unit (OTU). In one embodiment, the present invention may comprise a method for preparing a bioindicator for the analysis of a biosystem of interest comprising the steps of: preparing a nucleic acid sample comprising a plurality of DNA molecules from an ecosystem of interest; determining the sequence of at least some of the plurality of DNA molecules in the isolated DNA sample; grouping the DNA sequences into operational taxonomic units (OTUs); and identifying at least one nucleic acid sequence that is specific to a single OTU.
DNA from a variety of ecosystems may be used to develop bioindicators. In one embodiment, the ecosystem may comprise a body of water. For example, water from freshwater lakes may be used. Additionally or alternatively, water from estuaries may be used. Additionally or alternatively, water from other types of biosystems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
The method may utilize bioindicators that are shared among biosystems, and/or bioindicators that are specific to one, or a few, biosystems. Thus, a plurality of bioindicators may be developed. The bioindicators may be used as a means to analyze biosystems of interest. In one embodiment, the method may comprise the step of identifying the distribution of at least one of the OTUs in at least two ecosystems of interest.
Once the DNA molecules have been categorized and grouped by OTU, the sequences of the DNA molecules in each of the OTUs may be used to develop the collection of bioindicators as an assay system. Thus, the method may comprise preparing a collection of bioindicators wherein at least one of the OTUs comprises sequences that are unshared between at least two of the ecosystems of interest. Additionally and alternatively, the method may comprise preparing a collection of bioindicators wherein at least one of the OTUs comprises sequences that are shared between at least two of the ecosystems of interest.
The method may also include a step of immobilizing a plurality of oligonucleotide bioindicators at known locations on a substrate to form an array, wherein each oligonucleotide has a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU). In one embodiment, at least one of the OTUs comprises sequences that are shared between at least two of the ecosystems of interest. Alternatively or additionally, at least one of the OTUs may comprise sequences that are unshared between at least two of the ecosystems of interest.
The oligonucleotides immobilized on the array should be of sufficient length to provide specific hybridization to nucleic acid molecules isolated from various water samples that are used to probe the array. The immobilized oligonucleotides may be at least 20 nucleotides in length. In alternate embodiments, the immobilized oligonucleotides may range from about 30 to 200, or from 40 to 100 nucleotides in length. In one example embodiment, the immobilized oligonucleotides are each about 50 nucleotides in length. Specific hybridization does not require a perfect match between the oligonucleotide immobilized on the array and the ecosystem sample used to probe the array. As used herein, specific hybridization comprises hybridization such that a nucleic acid molecule isolated from the ecosystem of interest hybridizes to a single location (i.e., a single oligonucleotide sequence) on the array. As is known in the art, specific hybridization does not require that the immobilized oligonucleotide and the DNA sequence from the sample comprise perfect complementarity, but may allow for a mismatch at one or several base pairs. The level of mismatch will be determined at least in part by the sequence and length of the oligonucleotide immobilized on the array, as well as the hybridization conditions.
Also, the amount of the oligonucleotide immobilized on the array should be sufficient to allow detection of complementary nucleic acid sequences by the array, but in an amount such that background hybridization to unrelated sequences is avoided. In alternate embodiments, the oligonucleotides immobilized on the array range from about 1 fg to about 10 μg, or from about 50 fg to about 10 ng, or from about 0.5 pg to 1,000 pg, or from about 2 pg to 200 pg, or from about 8 pg to about 50 pg, at each location.
The operational taxonomic units may utilize variable ribosomal DNA (rDNA) sequences as a means to detect specific organisms. Thus, the immobilized oligonucleotides may comprise eukaryotic ribosomal DNA sequences, and/or prokaryotic ribosomal DNA sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise pathogen-specific sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise novel sequences from as yet unidentified microbes.
The oligonucleotides immobilized on the array may be derived from sequences found by analysis of microbes present in various sources of water. In one embodiment, oligonucleotides having sequences specific to organisms found in freshwater lakes may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in estuaries may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in other types of water systems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
In one embodiment, at least one immobilized oligonucleotide comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof. In alternative embodiments, the array may comprise at least 10 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ. SEQ ID NO: 113 or a fragment thereof, or at least 20 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 50 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 100 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof.
The bioindicators may be used to probe an array comprising nucleic acid sequences that are specific to organisms of interest. In one embodiment, the bioindicator may be evaluated to determine how the presence and/or absence of the bioindicator may correlate with a parameter of the ecosystem. Thus, the method may comprise using the polymerase chain reaction (PCR) to amplify a DNA sequence comprising a predetermined OTU. In one embodiment, at least one of the PCR primers comprises a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof. For example, the bioindicator may be used to probe an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU) so as to correlate the pattern of hybridization with a parameter that comprises at least part of the ecosystem. In an embodiment, the parameter comprises water quality.
Also, the method may use a first bioindicator from a particular microbe as an “entry point” for isolating other bioindicators from the microbe. Thus, in one embodiment, a bioindicator isolated from a portion of the genome of a microbe is used to identify a second bioindicator nucleic acid sequence from the same microbe. For example, the sequence of a first bioindicator nucleic acid molecule may be used to identify and isolate contiguous DNA sequence from the microbe that can serve as a bioindicator.
Embodiments of the present invention also comprise bioindicators isolated using the methods and systems of the present invention. In one embodiment, the present invention comprises a bioindicator, or a collection of bioindicators, for the analysis of an ecosystem of interest, wherein a bioindicator comprises an isolated nucleic acid having a sequence derived from a single predetermined microbial operational taxonomic unit (OTU). The bioindicator may comprise a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof. Or, in alternate embodiments, the collection of bioindicators may comprise at least 2, or 5, or 10, or 20, or 40, or 50 distinct nucleic acid sequences that individually comprise a sequence identical to SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof.
The present invention also comprises methods to monitor ecosystems. For example, one embodiment of the present invention may comprise a method for monitoring the water quality in a water sample of interest comprising measuring the hybridization of a nucleic acid sample from a water sample of interest to a plurality of oligonucleotides, and assessing at least one parameter of water quality based upon hybridization of the nucleic acid sample to the plurality of oligonucleotides. In one embodiment, an array of oligonucleotides is used. Thus, the plurality of oligonucleotides may be immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide.
In one embodiment, the method may comprise the steps of: generating an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU); preparing a nucleic acid sample from the ecosystem of interest; hybridizing the nucleic acid sample to the array; measuring hybridization of the nucleic acid sample to the array; and correlating hybridization of the nucleic acid sample to the array with a parameter that comprises at least part of the ecosystem.
In one embodiment, the ecosystem may comprise a body of water. For example, water from freshwater lakes may be used. Additionally or alternatively, water from estuaries may be used. Additionally or alternatively, water from other types of biosystems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
Where the ecosystem of interest comprises water, the parameter comprising at least part of the ecosystem may relate to the quality of the water. Thus, the parameter may relate to a quality that is important to evaluate if the water is suitable for drinking, cooking, bathing, agriculture, or other uses of water.
In one approach, the oligonucleotides are each selected to comprise different taxonomic units. Or, the oligonucleotides may be selected such that at least some are from the same microbial operational taxonomic unit (OTU).
The oligonucleotides immobilized on the array should be of sufficient length to provide specific hybridization to nucleic acid molecules isolated from various ecosystem samples that are used to probe the array. The immobilized oligonucleotides may be at least 20 nucleotides in length. In alternate embodiments, the immobilized oligonucleotides may range from about 30 to 200, or from 40 to 100 nucleotides in length. In one example embodiment, the immobilized oligonucleotides are each about 50 nucleotides in length.
Also, the amount of the oligonucleotide immobilized on the array should be sufficient to allow detection of complementary nucleic acid sequences by the array, but in an amount such that background hybridization to unrelated sequences is avoided. In alternate embodiments, the oligonucleotides immobilized on the array range from about 1 fg to about 10 μg, or from about 50 fg to about 10 ng, or from about 0.5 pg to 1,000 pg, or from about 2 pg to 200 pg, or from about 8 pg to about 50 pg, at each location.
The operational taxonomic units may utilize variable ribosomal DNA (rDNA) sequences as a means to detect specific organisms. Thus, the immobilized oligonucleotides may comprise eukaryotic ribosomal DNA sequences, and/or prokaryotic ribosomal DNA sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise pathogen-specific sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise novel sequences from as yet unidentified microbes.
The oligonucleotides immobilized on the array may be derived from sequences found by analysis of microbes present in various ecosystems of interest. In one embodiment, oligonucleotides having sequences specific to organisms found in freshwater lakes may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in estuaries may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in other types of water systems, such as tidal pools, wetlands, streams, rivers and salt water may be used.
In one embodiment, at least one immobilized oligonucleotide comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof. In alternative embodiments, the array may comprise at least 10 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 20 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 50 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 100 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof.
The array may be hybridized with a nucleic acid sample comprising at least one bioindicator that is isolated from the sample of interest. For example, PCR may be used to amplify rDNA sequences from genomic DNA from a water sample of interest, and the array used to probe those sequences. Alternatively or additionally, PCR may be used to amplify known pathogen-specific sequences from a water sample of interest, and the array used to probe those sequences. Alternatively and additionally, PCR may be used to amplify unidentified (i.e., novel) sequences specific to a water sample of interest, and the array used to probe those sequences. Alternatively or additionally, PCR may be used to amplify known non-pathogen specific sequences specific to a water sample of interest, and the array used to probe those sequences.
The bioindicator isolated from the ecosystem of interest may comprise nucleic acid sequences isolated from rDNA. In one embodiment, the nucleic acid sample hybridized to the array sequence comprises a plurality of rDNA sequences. For example, the nucleic acid sequence hybridized to the array may be generated using PCR primers derived at least in part from a ribosomal variable region so as to specifically amplify rDNA sequences. For example, the primers may comprise at least one oligonucleotide molecule having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof. In separate and alternative embodiments, the primers used for amplification of DNA from a sample of interest may comprise at least 10 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof, or at least 20 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof, or at least 40 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof. In one example embodiment, the primers used for amplification of a sample of interest include about 50 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof.
By measuring hybridization of the array to a sample from an ecosystem of interest, changes in at least one parameter that are indicative of a change in the ecosystem may be measured. Thus, in one embodiment, the present invention comprises a method for analyzing a pattern to evaluate the status of a biosystem comprising the step of measuring hybridization of a nucleic acid sample to an array of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU), and correlating the hybridization of the nucleic acid to the array with a parameter that comprises at least part of the ecosystem. In one embodiment, a single change in the pattern of hybridization to the array for a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest is associated with a change in one parameter. Or, a single change in the pattern of hybridization to the array for a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest may be associated with a change in a plurality of parameters. Additionally or alternatively, a plurality of changes in the pattern of hybridization to the array of a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest is associated with a change in one parameter. Or, a plurality of changes in the pattern of hybridization to the array of a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest may be associated with a change in a plurality of parameters. In one embodiment, the pattern analysis may comprise a computer program including known patterns such that samples may be analyzed using a computer. Samples may vary by location of the ecosystem, the time of sampling of a single ecosystem, or the location of sampling within a single ecosystem.
Embodiments of the present invention also comprise arrays of oligonucleotides for monitoring an ecosystem of interest. For example, one embodiment of the present invention comprises a device comprising an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU).
For example, in an embodiment the present invention comprises a device for monitoring water quality comprising an array, wherein the array comprises a plurality of oligonucleotides immobilized at known locations on a substrate, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU).
Also included as part of the present invention are systems for monitoring ecosystems of interest. Thus, another embodiment of the present invention comprises a system for monitoring an ecosystem of interest comprising an array comprising a plurality oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence that is derived from a single predetermined microbial operational taxonomic unit (OTU), and a device able to measure hybridization of the nucleic acid sample to the array. The system may further include a DNA sample comprising a plurality of nucleic acid sequences derived from an ecosystem sample of interest.
In one embodiment, the ecosystem analyzed using the devices and or systems of the present invention may comprise a body of water. For example, water from freshwater lakes may be used. Additionally or alternatively, water from estuaries may be used. Additionally or alternatively, water from other types of biosystems, such as tidal pools, wetlands, streams, rivers and salt water may be used.
The oligonucleotides immobilized on the array should be of sufficient length to provide specific hybridization to nucleic acid molecules isolated from various water samples that are used to probe the array. The immobilized oligonucleotides may be at least 20 nucleotides in length. In alternate embodiments, the immobilized oligonucleotides may range from about 30 to 200, or from 40 to 100 nucleotides in length. In one example embodiment, the immobilized oligonucleotides are each about 50 nucleotides in length.
Also, the amount of the oligonucleotide immobilized on the array of the devices and/or systems of the present invention should be sufficient to allow detection of complementary nucleic acid sequences by the array, but in an amount such that background hybridization to unrelated sequences is avoided. In alternate embodiments, the oligonucleotides immobilized on the array range from about 1 fg to about 10 μg, or from about 50 fg to about 10 ng, or from about 0.5 pg to 1,000 pg, or from about 2 pg to 200 pg, or from about 8 pg to about 50 pg, at each location.
The operational taxonomic units may utilize variable ribosomal DNA (rDNA) sequences as a means to detect specific organisms. Thus, the immobilized oligonucleotides may comprise eukaryotic ribosomal DNA sequences, and/or prokaryotic ribosomal DNA sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise pathogen-specific sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise novel sequences from as yet unidentified microbes.
The oligonucleotides immobilized on the array of the devices and/or systems of the present invention may be derived from sequences found by analysis of microbes present in various sources of water. In one embodiment, oligonucleotides having sequences specific to organisms found in freshwater lakes may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in estuaries may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in other types of water systems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
In one embodiment, at least one immobilized oligonucleotide comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof. In alternative embodiments, the array may comprise at least 10 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 20 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 50 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or at least 100 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5–SEQ ID NO: 113 or a fragment thereof.
The array devices and/or systems of the present invention may be hybridized with a nucleic acid sample that is isolated from the sample of interest. For example, PCR may be used to amplify rDNA sequences from genomic DNA from a water sample of interest, and the array used to probe those sequences. The nucleic acid sequence for hybridizing to the array may be generated using polymerase chain reaction (PCR) primers derived at least in part from at least one of a eukaryotic or prokaryotic ribosomal variable region. In an embodiment at least one of the PCR primers comprises a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof. In alternate embodiments, the PCR primers comprise at least 2, or 5, or 10, or 20, or 40, or 50 primers that individually have a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof. Alternatively or additionally, PCR may be used to amplify known pathogen-specific sequences from a water sample of interest, and the array used to probe those sequences. Alternatively and additionally, PCR may be used to amplify unidentified (i.e., novel) sequences specific to a water sample of interest, and the array used to probe those sequences. Alternatively or additionally, PCR may be used to amplify known non-pathogen specific sequences specific to a water sample of interest, and the array used to probe those sequences.
The present invention also provides methods for isolating samples from an ecosystem of interest that may be analyzed using molecular methods. Thus, in yet another embodiment, the present invention comprises a method to prepare a nucleic acid sample from a biosystem of interest, the nucleic acid sample comprising a plurality of bioindicator DNA sequences, wherein the method comprises amplifying a DNA sample isolated from a biosystem with a plurality of primers that have the ability to specifically amplify nucleic acid sequences comprising bioindicators. In one embodiment, at least some of the primers comprise at least a portion of a variable region of a ribosomal RNA. For example, the primers may comprise at least one oligonucleotide molecule having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof. In separate and alternative embodiments, the primers used for amplification of DNA from a sample of interest may comprise at least 10 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316, or a fragment thereof, or at least 20 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof, or at least 40 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316, or a fragment thereof. In one example embodiment, the primers used for amplification of a sample of interest include about 50 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof.
The present invention also comprises compositions for isolating samples from an ecosystem of interest that may be analyzed using molecular methods. Thus, in yet another embodiment, the present invention comprises an oligonucleotide having a sequence identical to any one sequence of SEQ ID NO: 114–SEQ ID NO: 316 or a fragment thereof.
The present invention may also comprise a method to identify microbes that are able to modify, or adjust to, an a particular ecosystem. In one embodiment, the method may comprise the steps of: (a) identifying a bioindicator that is associated with a particular microbe; (b) identifying the bioindicator in at least one ecosystem; and (c) correlating the presence of the microbe with a parameter specific to the ecosystem. The method may further comprise identifying the nature of the ability of the microbe to modify, or adjust to, the ecosystem. For example, the identification of a microbe whose presence shows an association with a particular toxin may indicate that the microbe has the ability to modify the toxin and/or modify the effect of the toxin on the environment.
Definitions
As used herein, the following terms shall have the definitions set out below. Also, in accordance with the present invention, conventional molecular biology, microbiology, and recombinant DNA techniques may be used that will be apparent to those skilled in the relevant art. Such techniques are explained fully in the literature (see, e.g., Maniatis, Fritsch & Sambrook, “Molecular Cloning: A Laboratory Manual (1982); “DNA Cloning: A Practical Approach,” Volumes I and II (D. N. Glover ed. 1985).
As used herein, “taxonomic unit” is a group of organisms that are considered distinct enough to be treated as a separate unit. A taxonomic unit may comprise a family, genus or species but is not limited as such. Also as used herein, each “operational taxonomic unit (OTU)” comprises a group of one or more microorganisms that are treated as a unit based on a SSU rDNA sequence identity of ≧97.5% among all members of the group.
As used herein, a bioindicator is an organism or part thereof, or a biological process, whose change in numbers, structure, or function points to a change, or a plurality of changes, in the environment. Generally, a bioindicator has a relatively high and easily identifiable sensitivity to selective environmental influences. The changes in the environment may relate to various changes in the ecosystem such as changes in a single chemical or chemical combinations in either absolute abundance or relative abundance to each other, changes in temperature, changes in biological populations, and the like. Any microbe whose relative abundance depends upon a biotic and/or an abiotic aspect(s) of biosystem of interest, or whose appearance is restricted to a subset of biosystems, is a bioindicator. Moreover, a plurality of two or more bioindicators (two or more present or more abundant than in the absence of a condition, two or more absent or less abundant than in the absence of the condition, or combinations of two or more in abundance and/or presence) may together indicate a condition of the ecosystem of interest. A condition of an ecosystem may refer to either a single biotic or abiotic factor or a combination of such factors.
A “vector” is a replicon, such as plasmid, phage or cosmid, to which another DNA segment may be attached so as to bring about the replication of the attached segment.
A “DNA molecule” refers to the polymeric form of deoxyribonucleotides (adenine, guanine, thymine, or cytosine) in either single stranded form, or a double-stranded helix. This term refers only to the primary and secondary structure of the molecule, and does not limit it to any particular tertiary forms. Thus, this term includes double-stranded DNA found, inter alia, in linear DNA molecules (e.g., restriction fragments), microbes, viruses, plasmids, and chromosomes.
DNA molecules may be identified by their nucleic acid sequences, which are generally presented in the 5′ to 3′ direction, wherein 5′ and 3′ indicate the linkages formed between the 5′-phosphate group of one nucleotide and the 3′-hydroxyl group of the next. As used herein, for a sequence presented in the 5′-3′ direction, its complement is the DNA strand which hybridizes to that sequence according to the Watson-Crick base pairing model. Thus, the sequence of the complement is defined by the sequence of the original strand, such that adenine base-pairs with thymine, and cytosine base-pairs with guanine.
The term “gene” means a region of DNA encoding for the mRNA sequence that codes for a given protein/polypeptide along with elements regulating mRNA expression, or a region of DNA encoding for a ribosomal RNA (rRNA) sequence that performs a structural function as a subunit of ribosomes along with elements regulating rRNA expression.
“Messenger RNA” or “mRNA” shall mean a RNA molecule that encodes for a polypeptide. “Ribosomal RNA” or “rRNA” shall mean a RNA molecule that performs a structural function in ribosomes.
“Complementary DNA” or “cDNA” shall mean the DNA molecule synthesized by polymerization of deoxyribonucleotides from an RNA template by an enzyme with reverse transcriptase activity.
An “isolated nucleic acid” is a nucleic acid the structure of which is not identical to that of any naturally occurring nucleic acid or to that of any fragment of a naturally occurring genomic nucleic acid spanning more than three separate genes. The term therefore covers, for example, (a) a DNA which has the sequence of part of a naturally occurring genomic DNA molecule but is not flanked by both of the coding sequences that flank that part of the molecule in the genome of the organism in which it naturally occurs; (b) a nucleic acid incorporated into a vector or into the genomic DNA of a prokaryote or eukaryote in a manner such that the resulting molecule is not identical to any naturally occurring vector or genomic DNA; (c) a separate molecule such as an oligonucleotide, a genomic fragment, a fragment produced by polymerase chain reaction (PCR), or a restriction fragment; and (d) a recombinant nucleotide sequence that is part of a hybrid gene, i.e., a gene encoding a fusion protein.
“Oligonucleotide”, as used herein, is defined as a molecule comprised of two or more deoxy- or ribonucleotides, preferably more than eight. Its exact size will depend upon many factors which, in turn, depend upon the ultimate function and use of the oligonucleotide. As is known in the art, it is possible that each of the olignucleotide molecules may vary by a few bases. For example, the synthesis of the oligonucleotide may result in a portion of the oligonucleotides being less than full length. Or, a portion of the oligonucleotides immobilized at a particular location may degrade by a small percentage over time. Such oligonucleotides are considered to be “fragments” of the original oligonucleotide. Thus, an oligonucleotide sequence that is derived from, and specific to, a single, individual OTU may include fragments of that oligonucleotide.
A “DNA fragment” includes polynucleotides and/or oligonucleotides and refers to a plurality of joined nucleotide units formed from naturally-occurring bases and cyclofuranosyl groups joined by native phosphodiester bonds. This term effectively refers to naturally-occurring species or synthetic species formed from naturally-occurring subunits. “DNA fragment” also refers to purine and pyrimidine groups and moieties which function similarly but which have non naturally-occurring portions. Thus, DNA fragments may have altered sugar moieties or inter-sugar linkages. Exemplary among these are the phosphorothioate and other sulfur containing species. They may also contain altered base units or other modifications, provided that biological activity is retained. DNA fragments may also include species that include at least some modified base forms. Thus, purines and pyrimidines other than those normally found in nature may be so employed. Similarly, modifications on the cyclofuranose portions of the nucleotide subunits may also occur as long as biological function is not eliminated by such modifications.
The term “identical” refers to sequence identity between two amino acid sequences or between two nucleic acid sequences. Percent identity can be determined by aligning two sequences and refers to the number of identical residues (i.e., amino acid or nucleotide) at positions shared by the compared sequences. Sequence alignment and comparison may be conducted using the algorithms standard in the art (e.g. Smith and Waterman, Adv. Appl. Math. 2:482 (1981); Needleman and Wunsch, J. Mol. Biol. 48:443 (1970); Pearson and Lipman, Proc. Natl. Acad. Sci. (USA), 85:2444 (1988)) or by computerized versions of these algorithms (Wisconsin Genetics Software Package Release 7.0, Genetics Computer Group, 575 Science Drive, Madison, Wis.) publicly available as BLAST and FASTA. Also, ENTREZ, available through the National Institutes of Health, Bethesda Md., may be used for sequence comparison. In one embodiment, percent identity of two sequences may be determined using GCG with a gap weight of 1, such that each amino acid gap is weighted as if it were a single amino acid or nucleotide mismatch between the two sequences.
“Primer” shall refer to an oligonucleotide, whether occurring naturally or produced synthetically, which is capable of acting as a point of initiation of DNA synthesis when placed under conditions in which synthesis of a primer extension product, which is complementary to a nucleic acid strand, is induced, i.e., in the presence of nucleotides and an inducing agent such as a DNA polymerase and at a suitable temperature and pH. The primer may be either single-stranded or double-stranded and must be sufficiently long to prime the synthesis of the desired extension product in the presence of the inducing agent. The exact length of the primer will depend upon many factors, including temperature, the source of primer and the method used. For example, for multiplex PCR amplification of genomic DNA, the oligonucleotide primer typically contains 15–30 or more nucleotides, although it may contain fewer nucleotides.
The primers herein are selected to be “substantially” complementary to different strands of a particular target DNA sequence. This means that the primers must be sufficiently complementary to hybridize with their respective strands. Therefore, the primer sequence need not reflect the exact sequence of the template. For example, a non-complementary nucleotide fragment may be attached to the 5′ end of the primer, with the remainder of the primer sequence being complementary to the strand. Alternatively, non-complementary bases or longer sequences can be interspersed into the primer, provided that the primer sequence has sufficient complementarity with the sequence or hybridize therewith and thereby form the template for the synthesis of the extension product.
“Probe” shall refer to any oligonucleotide that can be immobilized at individual addresses on the array. Such probes are single-stranded DNA molecules. The act of “probing” as used herein describes the step of hybridizing a nucleic acid sample with a probe having a known sequence, or a plurality of probes having known sequences (i.e., an array), to determine whether any of the sequences in the sample are complementary to the probe sequence(s).
As used herein, the term “hybridization” refers generally to a technique wherein denatured RNA or DNA is combined with complementary nucleic acid sequence that is either free in solution or bound to a solid phase. As recognized by one skilled in the art, complete complementarity between the two nucleic acid sequences is not a pre-requisite for hybridization to occur. Hybridization conditions can be described as ranging from low to high stringency. Hybridization that occurs under high stringency conditions is specific in that a large percentage of complementarity between two nucleotide molecules is required for hybridization to occur under stringent conditions. Hybridization that occurs under low stringency conditions is less specific in that a lower percentage of complementarity between two nucleotide molecules is required for hybridization to occur under stringent conditions. Even under highly stringent conditions, there may not be perfect complementarity between two oligonucleotide molecules that hybyridize. Generally, highly stringent conditions refer to washing hybrids in low salt buffer at high temperatures. Hybridization may be to filter bound DNA using hybridization solutions standard in the art such as 0.5M NaHPO4, 7% sodium dodecyl sulfate (SDS) at 65° C., and washing in 0.25 M NaHPO4, 3.5% SDS followed by washing 0.1×SSC/0.1% SDS at a temperature ranging from room temperature to 68° C. depending on the length of the probe (see e.g. Ausubel, F. M. et al., Short Protocols in Molecular Biology, 4th Ed., Chapter 2, John Wiley & Sons, N.Y). For example, a high stringency wash comprises washing in 6×SSC/0.05% sodium pyrophosphate at 37° C. for a 14 base oligonucleotide, or at 48° C. for a 17 base oligonucleotide, or at 55° C. for a 20 base oligonucleotide, or at 60° C. for a 25 base oligonucleotide, or at 65° C. for a nucleotide probe about 250 nucleotides in length. Equivalent stringencies may be obtained with other wash solutions by varying the temperature as is known in the art. Nucleic acid probes may be labeled with radionucleotides by end-labeling with, for example, [γ-32P]ATP, or by incorporation of radiolabeled nucleotides such as [α-32P]dCTP by random primer labeling. Alternatively, probes may be labeled by incorporation of biotinylated or fluorescein labeled nucleotides, and the probe detected using antibodies to the label, or by chemical incorporation of cyanin dyes as described herein.
As used herein, “restriction endonucleases” and “restriction enzymes” shall refer to bacterial enzymes that cleave double-stranded DNA at or near a specific nucleotide sequence.
A polypeptide refers to any peptide generated from a protein or the full-length protein itself. A polypeptide may include the full-length protein or a fragment generated by proteolytic cleavage, chemical cleavage, or other means.
As used herein, an array or microarray is a solid-state grid containing short sequences of nucleic acid (usually DNA) of known sequence fixed at a particular position (i.e., location or address) on the grid. DNA arrays are usually termed microarrays due to the small size of the grid and the small amounts of nucleotide (e.g., μM or nM amounts) present at each address.
As used herein, a computer program comprises a computer-encoded language that encodes the steps required for the computer to perform a specific task or tasks.
Also, as used herein, software comprises the computer program(s) used in conjunction with any other operating systems required for computer function.
As used herein, the singular forms “a”, “an” and “the” include plural references unless the context clearly dictates otherwise.
Water Surveillance Using Nucleic Acid Based Arrays
The present invention recognizes that the abundance of certain microorganisms may be affected by local water conditions. These conditions may vary for individual species and strains. For example, whereas one species might proliferate in phosphate-rich water, another species may prefer low-phosphate water (Kilham et al, 1986, Limnol. Oceanogr., 31:1169–1181; Siver et al., 1999, Limnol. Oceanograph., 44:1928–1955). Also, phytoplankton and benthic algae may be used as indicators of eutrophication (Shubert, L. E. (ed.), 1984, Algae as ecological indicators. Academic Press, N.Y; Stoermer, E. F. and J. P. Smol, 1999, The Diatoms: applications for the environmental and earth sciences, Cambridge Univ. Press, Cambridge, UK). Or, the abundance of known microbial species can vary as a function of pollution levels (Lemke et al., 1997, Microb. Ecol., 34:224–231). It has been shown that the presence of high levels of heavy metals in water may be reflected in the tissue of the marine limpet (Pérez-López, M., et al., 2003, Journal of Environmental Health, Part A—Toxic/Hazardous Substances and Environmental Engineering, 38:2845–2856). Also, coliform bacteria may be used as an indicator of the presence of human sewage in aquatic systems.
Over the past decade, direct observation and culturing of microbes has been complemented by emerging molecular approaches, including: in situ hybridization (Schöhuber, W., et al. 1991, Appl. Environ. Microbiol. 65:1258–1267), selective PCR detection of individual taxa (e.g. Oldach, D. W., et al. 2000, Proc. Natl. Acad. Sci. USA, 97:4303–4308; Rublee, P. A., et al. 2001, Environ. Health Perspectives, 109 [Supplement 5]:765–767), community assays such as Differential Gradient Gel Electrophoresis (DGGE) analyses (e.g., Díez, B., et al. 2001, Appl. Environ. Microbiol., 67:2942–2951) and filter macroarray hybridization (e.g., Rudi, K., et al. 2000, Appl. Environ. Microbiol., 66:4004–4011). In situ hybridization allows taxon-specific identification and enumeration of target organisms. Although highly specific, the method is time consuming as it generally involves microscopic observation of the sample. PCR, the polymerase chain reaction, may detect a targeted organism that exists in low abundance in the natural environment. Selective PCR detection of individual microbes is highly specific, rapid, and may even be quantitative (e.g., real-time quantitative PCR), but may be limited in that primers specific to the sequence to be amplified must be available. DGGE analysis has become a relatively common approach to community assessment of prokaryotic or even eukaryotic communities, but is limited in that it relies on the assumption that different nucleic acid sequences will display differential mobility in a gradient gel, which is not always the case.
From the standpoint of environmental investigations, recent microarray development efforts have increasingly focused on the identification of genes from specific microbial organisms associated with environmental processes, such as nitrogen fixation, or with the detection of specific microbes (Wu et al., 2001, Appl Environ. Microbiol., 67:5780–5790). Most of the microbes that exist in freshwater sources, however, are unknown and/or unculturable (Kaeberlein et al., 2002, Science, 296:1127–1129; Hiorns et al., 1997, Appl. Evnviron. Microbiol., 63: 2957–2960; Lopez-Garcia et al., 2001, Nature, 409:603–607).
A first step of developing methods and systems to monitor water may be the identification of suitable bioindicator molecules. For example, one aspect of developing an array to monitor a water supply is to develop nucleic acid sequences that are diagnostic of the aqueous microbial population.
The bioindicator may comprise the microorganism itself, or a molecule that provides information about the microorganism. The bioindicator may comprise a nucleic acid molecule. Nucleic acid molecules may be useful as bioindicators as nucleic acid molecules comprise a source of qualitative and quantitative information. By analyzing the sequence of the DNA molecules in the water sample, information about the genetic make-up of the microbes present in the sample may be obtained. Also, by measuring the amount of DNA molecules in the water sample, information about the amount of specific microbes in the sample may be obtained. As described herein, nucleic acid molecules, such as DNA, may be used to identify and classify microorganisms into operational taxonomic units (OTUs). Thus, the method may comprise the step of isolating nucleic molecules from the water sample 6.
The method may next comprise the step of determining the sequence of DNA molecules isolated from the sample of interest 8. In an embodiment, rDNA may be used as diagnostic sequences. Thus, to make an array for monitoring water, a first step may comprise the isolation and sequence characterization of 16S rDNA (prokaryotic) and 18S (eukaryotic) rDNA species from selected water reservoir samples. The DNA molecules selected for analysis may comprise small subunit (SSU) ribosomal RNA genes (SSU rDNA). In this way, recovery of DNA sequences may be based on the endogenous abundance of individual microbes, and is not restricted to the recovery of known microorganisms.
The DNA sequences isolated from the ecosystem of interest may be used to generate bioindicator probes. In one embodiment, the bioindicator probes are categorized into operational taxonomic units (OTUs) 10. Both prokaryotic and eukaryotic SSU rDNA can be useful targets for determination of operational taxonomic units because SSU rDNA sequences contain highly conserved nucleotide regions interspersed with variable regions. The conserved sequences provide an anchor by which a plurality of different rDNA sequences may be isolated from a sample. By using primers that hybridize to the conserved regions of either eukaryotic or prokaryotic rRNA genes, a library of amplified rDNA sequences that are different in the variable regions may be isolated from a single sample. Primers that may be used for amplification of prokaryotic rDNA sequences may comprise SEQ ID NOS: 1 and 2 (Table 1). Primers that may be used for amplification of eukaryotic rDNA sequences may comprise SEQ ID NOS: 3 and 4 (Table 1).
TABLE 1
Sequences and target positions of primers used to amplify rRNAs
SEQ
ID
Primer
Sequence
NO:
Location
16S
AGAGTTTGATCCTGGCTCAG1
1
8–272
Forward
16S
AAGGAGGTGATCCAGCCGCA1
2
1541–15222
Reverse
18S
AACCTGGTTGATCCTGCCAGT3
3
1–214
Forward
18S
TGATCCTTCTGCAGGTTCACCTAC3
4
1795–17724
Reverse
1Primers from Edwards et al., 1989, Nucleic Acids Res., 17, 7843–7853; Bruce et al., 1992, Appl. Environ. Microbiol., 58, 3413–3416.
2Position in E. coli (Brosius et al., 1981, J. Mol. Biol., 148, 107–127).
3Primers from Medlin et al., 1988, Gene 71, 491–499.
4Position in S. cerevisiae (Rubstov et al., 1980, Nucl. Acids Res., 8, 5779–5794).
The amplified rDNA products may be used to provide a foundation for phylogenetic classification and comparison of both prokaryotic and eukaryotic microbial species isolated from the water samples of interest (see e.g., McCaig, A. E., et al., 1999, Appl. Environ. Microbiol., 65:1721–173036, Reysenbach, A. L., et al., 1992, Appl. Environ. Microbiol., 58:3417–3418; Pace et al., 1986, Adv. Microb. Ecol., 9:1–55; Sogin and Gunderson, 1987, Annals. NY Acad. Sci. 503:125–139). A level of 97.5% sequence identity is a generally accepted criterion by which rDNAs may be placed in the same operational taxonomic unit (OTU). Because multiple small subunit rDNAs may reside within a genome for any single species (Farrelly et al., 1995, Appl. Environ. Microbiol. 61:2798–2801), a 97.5% level of sequence identity generally allows for the possibility that sequences in the same species are recovered. In performing this type of analysis, it may be necessary to check for artifactual sequences resulting from the amplification protocol (e.g., CHIMERA-CHECK; Kopzcysnski et al., 1994, Appl. Environ. Microbiol., 60:746–748; Wang and Wang, 1995, Appl. Environ. Microbiol., 63:4645–4650; Qui et al., 2001, App. Environ. Microbiol., 58: 2717–2722).
The present invention recognizes that the sequences of small subunit rRNAs in prokaryotes and eukaryotes may allow for phylogenetic classification of known and novel species as operational taxonomic units (OTUs). For example,
The sequences of rDNAs from isolated samples may be used to generate phylogenetic trees. In one embodiment, the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) may be used to compare the sequence data from OTUs and to generate a phylogenetic tree. This type of analysis may be used to confirm the relationship between known sequences, and to order newly identified sequences and OTUs. For example,
The sequence information may also permit the development of species specific primers. Species-specific primers may be used to characterize a variety of prokaryotic and eukaryotic microbes such as cyanobacteria, Mycobacterium, Pfiesteria piscicida, and other types of microbial species (see e.g., Edwards, U., et al., 1989, Nucleic Acids Res., 17:7843–7853; Reysenbach, A. L., et al., 1992, Appl. Environ. Microbiol., 58:3417–3418; Shi, W., et al., 2002, Appl. Environ. Microbiol., 68:3859–3866; and O'Brien, W. J., et al., 1997, The Limnology of Toolik Lake, p. 61–106, In: Freshwaters of Alaska—ecological syntheses, A. M. Milner and M. W. Oswood (eds), Springer-Verlag Publishers, New York, N.Y.).
Bioindicators may be unique to a specific biosystem, or may be shared among a plurality of biosystems. A diversity of microbial species may be readily retrievable even from a single body of water. Also, while any one body of water may have several unique OTUs, it is highly likely that the sample will include OTUs that are common to other biosystems. Such common OTUs may represent 10% or more of the rDNAs analyzed in the sample, and may be shared across water samples. Also, an environmental event that occurs in an environmental community, such as a contamination, may alter the abundance of individual microbial species and related bioindicators in that community. The method may therefore comprise the step of determining whether an operational taxonomic unit (OTU) and/or an individual or species-specific DNA sequence is specific to a particular ecosystem, or varies in abundance between ecosystems. For example, a bioindicator for assessing freshwater microbial communities may comprise nucleic acid sequences that are characteristic of the freshwater system, or that are diagnostic of the response of microbes to certain changes in the fresh water environment. Or, a bioindicator for assessing marsh water microbial communities may comprise nucleic acid sequences that are characteristic of the marsh environment, or that are diagnostic of the response of microbes found in the marsh environment to certain changes in a marsh water environment. Thus, referring back to
To determine which OTUs, if any, appear in more than one ecosystem, the sequences from a library of DNA sequences isolated from a biosystem of interest may be compared to those sequences in every other library from biosystems of interest in pairwise library comparisons, and a similarity coefficient may be calculated for each pairing. For example, in an analysis of five different samplings of DNA molecules from three different lakes (Lake Townsend, NC; City Lake, NC; and Toolik Lake, AK) there was some overlap between every pair of samples. There were also notable differences between the lakes. For example, none of the prokaryotic sequences were shared between Lake Townsend, a mesotrophic lake in North Carolina, and Toolik Lake, an oligotrophic lake in Alaska.
Venn diagrams may be used depict sample comparisons at different spatial and temporal scales to identify sequences that may differ between biosystems. Referring now to
Once the nucleic acid sequences isolated from various ecosystems have been identified and compared, it may be possible to compile OTUs as putative bioindicators 14 (
The method may next comprise the step of organizing a nucleic acid array that can reflect microorganisms that are common to multiple communities, as well as organisms that are specific to one or only a few communities to thereby monitor the effect of an ecological change 16. Thus, the ability to assess environmental parameters of water quality may require a sufficient number of bioindicator species that have unique profiles in different ecosystems, but may also require species that are shared among samples to allow for general application.
The array may comprise nucleic acids that are specific to known organisms. Additionally or alternatively, the array may comprise nucleic acids that are grouped to provide information about various taxonomic groups. For example, the array may comprise a plurality of prokaryotic and/or eukaryotic nucleic acid sequences derived from specific rDNAs. Or, the array may comprise a plurality of nucleic acid sequences organized by operational taxonomic unit. Notably, there is no requirement that the environmental DNA samples used to develop the array are the same as the environmental communities to be analyzed.
Samples that are derived from very different environmental communities may be expected to vary more than samples that are derived from similar communities, or the same community. Still, samples taken from a single lake, but either at a different location, or a different season, may also show variation (e.g.,
Next, the method may comprise the step of isolating a sample from an ecosystem of interest 22. In one embodiment, the ecosystem may comprise water. Samples may be collected from one body of water at different levels, or at different locations, and/or during different times of the year. Also, samples from different bodies of water may be used. For example, samples may be collected from different lakes, pools, estuaries, or marshes. Or, bodies of water comprising different types of growth levels may be used (e.g., eutrophic, mesotrophic, or oligotrophic). Or, samples may be obtained from a body of water because there is a reason to suspect that the body of water has been contaminated in some way.
The method may next comprise the step of preparing a DNA sample from the ecosystem of interest 24. For example, the polymerase chain reaction (PCR) may be used to amplify DNA sequences from a water sample of interest. The PCR amplification may use primers designed to amplify sequences that, if present in the sample and amplified, are complementary to the sequences on the array. In that way, if a sequence on the array is present in the sample of interest, it may be detected. In one example, a multiplex (i.e., multiple primer) PCR amplification is used to amplify multiple sequences from the sample of interest that are complementary to sequences immobilized on the array. Primer pairs that may be used for multiplex PCR may include a sequence selected from the group of SEQ ID NO: 114–SEQ ID NO: 316.
The amplified DNA molecules from the sample of interest may be then labeled in some manner 26. For example, the amplified DNA molecules may be labeled by the chemical incorporation of a fluorescent dye(s) as described herein.
Next, the method may comprise the step of hybridizing the labeled DNA sample from the ecosystem of interest to the array 28. In one embodiment, a high stringency hybridization is used. For example, the hybridization conditions may comprise the conditions as described herein.
The presence of sequences in the sample of interest that are complementary to putative bioindicator sequences on the array may be determined by measuring locations on the array that exhibit hybridization to the labeled probe 30. In this way, the identity, and in some cases, the relative amounts, of sequences that are in the sample may be determined.
The method may then comprise the step of correlating hybridization of the DNA sample to the array with a parameter that comprises at least part of the ecosystem. For example, if two samples of water (e.g., sample A and sample B) are hybridized to the same array, and different hybridization patterns result, than the oligonucleotide(s) on the array that displays a change in hybridization may correspond to a DNA sequence(s) that is diagnostic of a difference, or a plurality of differences between the two samples. Thus, the method may comprise the step of determining whether the pattern of hybridization at any one position or at a plurality of positions on the array changes 32.
In one embodiment, no change in the pattern of hybridization at any one position or at a plurality of positions on the array is detected upon hybridization with two different samples. In this, case, no change in water quality is detected, and no action is required 34. Alternatively, a change in the pattern of hybridization at any one position or at a plurality of positions on the array is detected upon hybridization with two different samples. In this case the change in the water quality may be recorded 36 and the nature of the change determined 38 such that appropriate action may be taken.
An example of the application of pattern analysis to the evaluation of a biosystem is shown in
Still referring to
As described herein, primers that may be used for amplification of bioindicator nucleic acid molecules from an ecosystem may be designed to amplify sequences from the variable regions of rDNA. Small subunit rRNA genes (SSU rDNA) are especially useful targets for the molecular identification of microbial species because these sequences contain highly conserved nucleotide regions interspersed with variable regions. The variable regions may be used as a foundation for phylogenetic classification and comparison of both prokaryotic and eukaryotic microbial species (e.g., Sogin and Gunderson, 1987, Annals. NY Acad. Sci., 503:125–139). The sequence information also permits detection and quantification of microbial species by PCR amplification using species-specific primers.
Thus, in one embodiment, ribosomal DNA that includes highly conserved and highly variable regions is used to characterize the presence of microbial community members. Species-specific or OTU-specific primers that anneal to internal variable regions can then be used to test for the presence of individual species. For both eukaryotic and prokaryotic rDNA, the variable rDNA regions show sufficient variability to develop amplification primers and probes that may be sensitive and specific to the organism to be tested.
For increased specificity and sensitivity in microarray experiments, variable sequence regions within the SSU rDNA may be utilized in a two-tiered strategy: (1) species-specific or OTU-specific PCR primers (e.g., Tables 2 and 3) can be multiplexed in individual PCR reactions to selectively amplify individual species or OTUs; (2) PCR products may then be labeled and hybridized to corresponding species-specific or OTU-specific oligonucleotide probes (e.g., Tables 2 and 3) immobilized on a microarray, where the probes immobilized on the array have sequences that are included in the amplified DNA products. The process may provide improved specificity and sensitivity because each of the species-specific or OTU-specific primer pairs and probes are designed using the same rDNA sequence.
To determine nucleic acid sequences that are specific to a single OTU, and thus can be used to detect the presence of a specific OTU in an ecosystem of interest, water samples were used to isolate DNA sequences derived from microbial ribosomal DNA. The individual ribosomal DNAs were cloned and the nucleic acid sequence for each clone was determined. Then, sequences from each rDNA clone were simulataneously aligned with either a prokaryotic rDNA sequence or a eukaryotic rDNA sequence to determine regions of variability for the cloned rDNAs. In this way, primers and probes (e.g., Tables 2 and 3) specific a particular OTU (or microbe population) were identified.
To ascertain the relative location and degree of variability among variable regions, rDNA sequences can be initially aligned using the multiple alignment computer program CLUSTAL W (Thompson et al., 1994, Nucleic Acids Res., 22:4673–4680). Multiple alignment parameters including a gap initiation penalty of three, a gap extension penalty of one, a base match score of one, and a base mismatch penalty of one were used. Transitions were not weighted and terminal gaps were not penalized. By aligning the cloned sequences with either the prokaryotic or eukaryotic rDNA, the SSU rDNA was demarcated into conserved and variable sequence regions, which were further aligned by hand to optimize the multiple alignment result where necessary. For prokaryotic primer sequences and probes (Table 3), variable sequence regions were used within nucleotides 50–880 (V1, V2, V3, and V4), based on alignments with E. coli rDNA (SEQ ID NO: 317) (
Thus, in one embodiment of the present invention, amplification of a genomic sample DNA may be performed by multiplex PCR using primers chosen to provide products that can hybridize to taxon-specific ribosomal DNAs. Using this protocol can dramatically reduce non-specific labeling, and eliminate the need for intermediate PCR reactions, which reduce sensitivity. Oligonucleotide probes that may be spotted to provide a taxon-specific array (e.g., SEQ ID NOS: 5–113), and the primers used to detect (i.e., amplify) such sequences in water samples (e.g., SEQ ID NOS. 114–316), are shown in Tables 2 and 3. For example, primers having the sequences SEQ ID NOS. 114 and 115 (1F and 1R, respectively) may be used to amplify DNA from a water sample such that the amplification product contains sequences that will hybridize with an oligonucleotide probe (1P) immobilized on an array, where probe 1P has the sequence described by SEQ ID NO: 5. In one embodiment, multiple primer pairs (e.g., SEQ ID NOS: 114–214) are used to amplify DNA sequences that include SEQ ID NOS: 5–60). In addition, as is known in the art, the reverse complementary sequence of each probe sequence in Tables 2 and 3 may also be spotted as an oligonucleotide on the array.
TABLE 2
Eukaryotic probes and primer pairs used for multiplex PCR
Eukaryotic
SEQ
GenBank
SEQ
primer sequence
ID
PCR
Accession
Probe Sequence
ID
Oligo
(5′–3′)
NO:
No.
Template
No.
(5′–3′)
NO:
No.
ATACAGGCGC
114
1F
Acanthamoeba
AY35164
ACTAACTCAATAGC
5
1P
TCGATAAGAG
mauritaniensis
7
AGGAACGGGAATC
AGCTGCTAGG
115
1R
CAGAAGGAGGGGA
GGAGTCATTC
CGGGCGGGCC
AACTCGACTTT
116
2F
Cryptosporidi
AF22299
GATTTCTCATAAGG
6
2P
ATGGAAGGG
um parvum
8
TGCTGAAGGAG-
CAAAGTCCCTC
117
2R
TAAGGAACAACCT
TAAGAAGAC
CCAATCTCTAGT
TTGGCTTTAGC
118
3F
Cyclospora
AF11118
AGTTCCGGAACACC
7
3P
CGGCGATAG
cayetanensis
3
AACGCACGCAGCG
AAGCCAAGGT
119
3R
AAGCGCGGAAGGC
AGGCGTTTCC
TACCGGAAGA
GACGACACAT
120
4F
Entamoeba
X65163
GAAATGTCTTATTG
8
4P
AACTCTAGAG
histolytica
ACATCCCCTCAGCA
TCATCCAATCC
121
4R
TTGTCCCATGCTTG
TTGGTTGAC
AATATTCA
AACTTGCCCAA
122
5F
Giardia
AF19944
CCCACGCGGCGGG
9
5P
TGCGCGG
intestinalis
9
TCCAACGGGCCTGC
GGGAATACGG
123
5R
isolate Dog19
CTGGAGCGCTCCCG
TGGTGTCTG
TTTCCTCGT
GATTGGAATG
124
6F
Isospora belli
AF10693
GAATTTCACCACGT
10
6P
ATGGGAATCC
5
ACACACCCCTAAG
AGGAGAAGTC
125
6R
GGCGGACTGGCTG
AAGTATGACG
CTTCCAGCAG
GCGGTAGTAA
126
7F
Microsporidiu
AY14064
CTTTATCATCGGAC
11
7P
GGAGACGTG
m sp. STF
7
TCGCCCCTGGCCAG
GCATCGGCATC
127
7R
CGCTTTCGCCTCTG
GTTTACTGC
TCGCTCCT
TTCGGTGGTGA
128
8F
Naegleria
AF33842
CCTCCAACCATCTC
12
8P
GGTATTATC
fowleri
3
CTGATGGAACTAGT
AAGATCGCTG
129
8R
TACCCCGTAAACAC
GGATAGTGTC
TCTTAGGT
ATCGAGTATCA
130
9F
OTU LT3A27,
N/A
ACGGAGACAAACA
13
9P
ATTGGAGGG
multi-copy,
AGCACCAACACAA
GACGGGGTCA
131
9R
identified as
GTGAAGGGCACGT
ATACAACGAC
Asterionella
TGCTCCAACCA
formosa
GCCAATGGTCT
132
10F
OTU LT1A42,
N/A
CAAGCAGAAAGGC
14
10P
TCTTATTGG
multi-copy,
ACGCGCGCACCGTC
GAGGTCGTAA
133
10R
identified as
CAACCAGAGGCTG
ATTGACACTC
Cryptomonas
ACAGTTCACA
sp., strain
M420
TTCAAACCGGC
134
11F
OTU LT1A4,
N/A
GCACGCGCATGCC
15
11P
CTCGTTCTG
multi-copy,
GTCCGACCAGAGG
CCCATAACCA
135
11R
identified as
CCGACAGCCCACA
ACGAAATAGC
Cryptomonas
CGCGCCCAAAA
ovata, strain
CCAP 979/61
TTAGCGAATCG
136
12F
OTU LT2A7,
N/A
TAACTGTCCCTGAT
16
12P
TGGCACGTC
multi-copy,
GGGACTAGTAGGG
AATGTATTCCT
137
12R
identified as
ATTGGTTTAAAGCC
GCAAACGCC
Dileptus sp.
TCTCCCTAG
GGGTTCTTACG
138
13F
OTU LT2A19,
N/A
TCTCAGACGGATGA
17
13P
AACTTTGGG
single-copy,
ACGCCTATACCTCG
CTGATCGGGCT
139
13R
identified as
ACCGGAGCCGCTGT
TGAAAGACC
Coleps sp.
ACAAACGC
TATCGAGGAC
140
14F
OTU LT3A2,
N/A
ACCTAATGCCACAC
18
14P
CAATTGGAGG
single-copy,
AGATTCCACCCAAG
GACGGAGTCA
141
14R
unidentified
GATGGACGAGCTG
ATACAACGAC
CCCAAGTAC
TGGACTCTTTT
142
15F
OTU LT1A3,
N/A
CCATCTGCGCCTCA
19
15P
GAGTCCGGC
single-copy,
ACATGCAGGTAAA
ATCAATACTAA
143
15R
unidentified
TCGTAAAGAAAAG
CACCCACCG
GCCAAATAGC
TAACGATAGC
144
16F
OTU LT1A10,
N/A
GTATCACACCAGG
20
16P
GGGCTCGTTC
multi-copy,
GAGGTTATTGAACG
CATAGGGTGCT
145
16R
unidentified
CAGACCACCTAGGT
GATAGAGTC
AACACCTAA
CCGAGATTTCT
146
17F
OTU LT2A12,
N/A
AAGGATGCTTTCAG
21
17P
CGGAAATTG
multi-copy,
GCACTGATCGCGCA
TTTCTCACGAG
147
17R
unidentified
CACTGAGGTGGGA
GTGCTGAGG
AGTGCCGTT
ATGGTGGAGG
148
18F
OTU TL1A16,
N/A
TAAGTGCAACGGG
22
18P
TGATTCATTC
multi-copy,
ATCCTCATGCAGAA
AATTGACATCC
149
18R
unidentified
AGACCCGAGCCTG
ACTGATCCC
CCGTCCGACC
GATACAGGAC
150
19F
OTU TL1A1,
N/A
AAAGTAAACCTGC
23
19P
TCATCCGAGG
multi-copy,
CAGCACAGACGGA
AAACGCCTGC
151
19R
unidentified
CACTCGGCGAAGA
AGATCGCTAG
GCACCCGCCTG
ACAATGCCGG
152
20F
OTU TL1A2,
N/A
TTAATGCCAGATAT
24
20P
GCCTTTCAAG
multi-copy,
GCTCTCCCCGAGGA
TGGAGTCGTTA
153
20R
unidentified
TGGCTGCAGACAC
CAAACTTCC
ATAGTACAG
TCGGCGACGA
154
21F
OTU TL1A9,
N/A
AGTCGACCAGTTCT
25
21P
TGATTCATTC
multi-copy,
GACCCATGAGGCC
TGAACAAACC
155
21R
unidentified
GACCGGCTGAGCTC
ACGCCCAATC
ACTCTGAAC
CGGTTTACCGG
156
22F
OTU TL1A12,
N/A
TCAAACCTGATTCA
26
22P
CGATAGATC
multi-copy,
AACCCGTATGGGTC
TTCTCTCGAGG
157
22R
unidentified
GATCGGTCGTCCTC
TGCTGAAGG
AGCAGAAA
AATCGGATCG
158
23F
OTU TL1A21,
N/A
TGGTAGGCTACCAC
27
23P
CATGGGCTAG
multi-copy,
TGCGCATCCACAAG
GAACGGGATA
159
23R
unidentified
GAGGCAGAAACTA
ATTCTCGCCC
GCCAACCAG
CCCACTTATGT
160
24F
OTU CL1A3,
N/A
GCTTCATGCAGGAG
28
24P
GGGTTTGAC
single-copy,
CATCTCAGCATCCA
GAAGTAGAGG
161
24R
unidentified
GTGTTGGGACCAG
ATCTTGCCTC
GACATACTG
GACAGCTTCTT
162
25F
OTU CL1A4,
N/A
GTTATGATTCTATC
29
25P
TAATGGAGG
single-copy,
TCAAGGAGGAGCG
ATCTGTTGGTC
163
25R
unidentified
TCCTGTGCTCTCCC
CTCCAAATC
ACTTCACTC
AATACAGGGC
164
26F
OTU CL1A5,
N/A
TCCAGAAGGTGAG
30
26P
TCTTTGAGTC
single-copy,
GCCGACGCAAAGA
AAGACGTACC
165
26R
unidentified
GTACTCACCGCTAG
ACCGATCCTG
GTGGACCCTC
TAACAATGCG
166
27F
OTU CL1A6,
N/A
AGAGTAAAGGACG
31
27P
GAGCCTTCGG
single-copy,
CAGGTCCGGACGC
AAGAACGTCC
167
27R
unidentified
CGACAAGTGAATG
GCCAATCCTG
CCGACGCCTTC
TATCTGGCGCT
168
28F
OTU CL1A8,
N/A
TCTCTAGAAGGATG
32
28P
TTTGCGTCG
multi-copy,
CCCAACCCGCACCG
CAACGTCTACC
169
28R
unidentified
GCACTCACAGGCC
CATCCCAAG
AAAAAGGCC
ACTCGGGAAC
170
29F
OTU LT2A20,
N/A
CGAAGACGGATGA
33
29P
CTAGTTCTAC
single-copy,
CTAACTATATACTG
TCTCTTACGGC
171
29R
unidentified
ACGTAAGCCAGCA
GCCGAAAAG
TATAAATAGC
AGGGCCAACG
172
30F
OTU LT1A5,
N/A
CACAATTAAGTGCA
34
30P
GTCTTGTTAT
multi-copy,
ACGGGATCCTCATG
TCGGAAATTGA
173
30R
unidentified
CAGAAAGACCCGA
CATCCACTG
GCCTGCCGT
CTCTCTCCGAG
174
31F
OTU LT1A8,
N/A
TATTAACGCACTAC
35
31P
TATCAATTG
multi-copy,
GCCCTGGAAGGAT
ACTTCCCTCAA
175
31R
unidentified
GCTTTCAGGCACTG
TCGCTAGTC
ATCGCGCAC
GCAGAGCTTC
176
32F
OTU LT1A9,
N/A
ACAGCTACCACCAC
36
32P
ACAGTTTTGC
single-copy,
CCTAAGGTGGGGA
AGACGTCTCCT
177
32R
unidentified
GGTCATCCCGATCA
GATCGCAAG
GAGATTCAA
N/A
OTU LT1A11,
N/A
TTCCAAGAGGATGC
37
33P
single-copy,
CTCGGTCTAACCAG
unidentified
ACACAAACCCGTAT
GGGTCGGT
N/A
OTU LT1A13,
N/A
AAGTGTTTTCCGGA
38
34P
single-copy,
AGATGGACGCAAA
unidentified
CACCCGGTACACA
GACCGCGAGT
ATACGTCCCGG
178
35F
OTU LT3A5,
N/A
TAACAGAAGGATG
39
35P
GACTGCAAT
multi-copy,
GTAGGGCGGCTCA
CGAAGGCGGA
179
35R
unidentified
GCGCACTCAACTTG
TAATTCTCGC
AGGGCAAAGT
ACAATGCAGG
180
36F
OTU LT3A6,
N/A
ACAGTACAAGTCTT
40
36P
GCCTTTACGG
multi-copy,
GCGACTAGACCGTC
GAATAACACT
181
36R
unidentified
CGGCCCAAAACCT
CACTGATCCC
GAAATCCAA
ATACAGGACT
182
37F
OTU LT3A7,
N/A
AAACAAGCCAGTA
41
37P
CATCCGAGGC
multi-copy,
CCGAAAGCATTCG
AAACGCCTGC
183
37R
unidentified
GACCGACTTCTGTC
AGATCGCTAG
CGCCGAGATC
N/A
OTU LT3A11,
N/A
GCAAGCGGATGAC
42
38P
single-copy,
TGTCAGAATCCCCG
unidentified
TCTAATGACTGAAG
ACCTGAACA
CTTTACAGGTC
184
39F
OTU LT3A13,
N/A
ACCTAATGCCACAC
43
39P
TGGCAATTG
single-copy,
AGATTCCACCCAAG
CATACAGTGCT
185
39R
unidentified
GATGGACGAGCTG
GACAGGGTC
CCCAAGTAC
CAGGGCCTTTT
186
40F
OTU LT1A1,
N/A
TTCAGAAAAGAAG
44
40P
CAGGTCTTG
multi-copy,
TGTCGTCCCGATCG
CACAAGGTGC
187
40R
unidentified
CACTACCGTAAGGC
CAACAGAGTC
GGCAAGCGT
AACAATGTCTG
188
41F
OTU LT1A38,
N/A
AATGCCGCTGGTCA
45
41P
GCCCTACGG
multi-copy,
CACGGAAGAAAGA
GTAAACAACG
189
41R
unidentified
AGCCGACCAAACA
CCCACCGATC
GTGCGACTTG
GAGGGCAAGT
190
42F
All LT1A &
N/A
N/A
CTGGTGCCAG
LT3A OTUs
TABLE 3
Prokaryotic probes and primer pairs used for multiplex PCR
Prokaryotic
SEQ
GenBank
SEQ
primer Sequence
ID
PCR
Accession
Prokaryotic probe
ID
Oligo
(5′–3′)
NO:
No.
Template
No.
Sequence (5′–3′)
NO:
No.
CGAATGGATT
191
43F
Bacillus
AB116124
GTGACAGCCGAA
46
43P
AAGAGCTTGC
anthracis strain:
GCCGCCTTTCAAT
TGCCAGCTTAT
192
43R
S51
TTTCGAACCATGC
TCAACTAGC
GGTTCAAAATGT
T
GAACGTACCA
193
44F
Brucella
AF220149
CCAACGCGGGCC
47
44P
TTTGCTACGG
melitensis
GATCATTTGCCG
ACCGTCATTAT
194
44R
ATAAATCTTTCCC
CTTCACCGG
CCGAAGGGCACA
T
ACGGGCTTCG
195
45F
Burkholderia
AY305760
AGGCCCGAAGGT
48
45P
GCCTGGTG
mallei strain
CCCCCGCTTTCAT
TCCGGGTATTA
196
45R
2000031063
CCTCAGATCGTAT
GCCAGAATG
GCGGTATTAATC
GCTTGCTAGAA
197
46F
Campylobacter
AF550630
TCCTACACCGAA
49
46P
GTGGATTAG
jejuni strain
AAACTTTCCCTAC
CGTCAGAATTC
198
46R
B99/206
TCAACTTGTGTTA
TTCCCTAAG
AGCAGGAGTATA
TTTAGTGGCGG
199
47F
Chlamydophila
AY334530
GGTCCGAAGATC
50
47P
AAGGGTTAG
psittaci clone
CCCTTCTTTAATA
ATCTCTCTTAT
200
47R
cvCps2
TGTTTTAGATGCC
TCCCAAGCG
TAAACATACCAC
AAGCTTCCTTC
201
48F
Clostridium
AY303799
CGCCGCGGGTCC
51
48P
GGGAAGTGG
botulinum strain
ATCTCAAAGCAA
GGTACCGTCAT
202
48R
AIP 355.02
TAAATCTTTGATA
TATCGTCC
AGAAAATCATGC
G
ATAACCTGGG
203
49F
Coxiella burnetii
Y11502
TCATCTTATAGCA
52
49P
GAAACTCGGG
strain Nine Mile
CGAGGTCCGAAG
CCAAGGATATT
204
49R
ATCCCCCGCTTTG
ACCCTTGAG
CTCCAAAGAGAT
AGAAGCTTGCT
205
50F
Escherichia coli
AB035920
ACATCCGATGGC
53
50P
TCTTTGCTG
O157:H7
AAGAGGCCCGAA
TTCCTCCCCGC
206
50R
GGTCCCCCTCTTT
TGAAAGTAC
GGTCTTGCGACG
T
CAATTCTGGGA
207
51F
Escherichia coli
NC 002655
CAATTCTGGGAA
54
51P
AGCGTGG
O157:H7
GCGTGGCATTAA
CGATGCATGAT
208
51R
EDL933
TACTGAATTGTCA
GATGACA
TCATCATGCATCG
N/A
Escherichia coli
NC 002655
GGTTGATGAAAA
55
52P
O157:H7
AGCATTTGGAGC
EDL933
CGCGAAATTTAC
CAGTGTCTTAAA
AC
N/A
Escherichia coli
NC 002655
TGTCCGATTCAGC
56
53P
O157:H7
ACGGGTAAATAG
EDL933
TCGTATTGTTAGT
GGCCGAATTTAA
N/A
Escherichia coli
NC 002655
TTGCTGGAGAGT
57
54P
O157:H7
CCTTCTCGGGTAT
EDL933
CGATTGTCGAAG
ATAAACATATTT
A
GTGGTGGATTA
209
55F
Escherichia coli
NC 002655
GTGGTGGATTAC
58
55P
CGCCATG
O157:H7
GCCATGACATGG
GCTATTACTCC
210
55R
EDL933
GAGGATTAACGG
CCCCCGT
GGGGGAGTAATA
GC
TCTGGAGTATC
211
56F
Escherichia coli
NC 002655
TCTGGAGTATCA
59
56P
AAGCACT
O157:H7
AGCACTTATAAC
CCAGGAAGAG
212
56R
EDL933
CTAATAACACAA
GGTTTTGT
AACCCTCTTCCTG
G
GCCCTGACGTA
213
57F
Escherichia coli
NC 002655
GCCCTGACGTAT
60
57P
TGGCGGG
O157:H7
GGCGGGTACGAA
GTAATGGTCAC
214
57R
EDL933
ATGAAGCCAGTG
CGTCACT
ACGGTGACCATT
AC
N/A
Escherichia coli
NC 002655
ACTGGCGGGAAC
61
58P
O157:H7
ACATGAAAACGT
EDL933
AACCACGCTACC
AGTAGCCAGAAG
AA
N/A
Escherichia coli
NC 002655
CCATTAAAACTA
62
59P
O157:H7
ATGCCTGTCATA
EDL933
ATGGAGGGGGAT
TCAGCGAAGTTA
TT
AAGACATCTTC
215
60F
Escherichia coli
NC 000913
AAGACATCTTCA
63
60P
ACCGTTC
K12
CCGTTCACGATAT
TCAGATTTCCC
216
60R
TTTGAAAGCACG
CTCGTGC
AGGGGAAATCTG
A
N/A
Escherichia coli
NC 000913
CACCGTCGCTTTA
64
61P
K12
AAACGCGCCCGG
TGGGAGAATCGT
CGTTGTACATTTA
N/A
Escherichia coli
NC 000913
TTTCTGATCGCGT
65
62P
K12
TGCTGCGCTGATC
AAAGAAGTAAAC
AAAGCAGCTTAA
ATGGCATCCGT
217
63F
Escherichia coli
NC 000913
ATGGCATCCGTG
66
63P
GGTATCC
K12
GTATCCCGACTCT
CACTTCACCGT
218
63R
GCTGCTGTTCAA
TTTTGAA
AAACGGTGAAGT
G
AACAGCTTGCT
219
64F
Shigella sonnei
X96964
N/A
GTTTCGCTG
TTCCTCCCCGC
220
64R
TGAAAGTAC
CAGGTCTTAGG
221
65F
Francisella
AY243028
AGGCTCATCCAT
67
65P
ATGCTGACG
tularensis strain
CTGCGACACGCC
AAGGCTATTA
222
65R
3523
GAAAGCCACCTT
ACCTTGAGGC
TAATCCACAGAT
AT
AGACTATCTAC
223
66F
Legionella
AJ496383
AATCCTTAAAAG
68
66P
TTCTGGTGC
pneumophila
TCGGTCGTAGTCC
ATACAGGTGCT
224
66R
serogroup 6
GGATTGGAGTCT
GCATGGCTG
GCAACTCGACTC
C
GAGTAGCAAT
225
67F
Leptospira
Z12817
ATCTCCGAGCAA
69
67P
ACTCAGCGGC
interrogans
TAAATCTTTACCC
TACCATCATCA
226
67R
GAAAAATCTTAT
CATTGCTGC
GATCTCTCGGGA
C
GAGCTTGCTCC
227
68F
Pseudomonas
AB117953
TCATCTGATAGC
70
68P
TGGATTCAG
aeruginosa
GTGAGGTCCGAA
GTAACGTCAA
228
68R
strain WatG
GATCCCCCACTTT
AACAGCAAGG
CTCCCTCAGGAC
G
AGTTAATTAGT
229
69F
Rickettsia
M21789
ATCTGACGCGGG
71
69P
GGCAGACGG
prowazekii
CCCATCCATCAG
ACTAAACCGC
230
69R
CGATAAATCTTTC
CTACGCACTC
CTCCGTAGAGAA
T
AGCTTGCTGCT
231
70F
Salmonella
Z49264
CTTGGTGAGCCG
72
70P
TTGCTGACG
typhimurium
TTACCTCACCAAC
TAACCACAAC
232
70R
AAGCTAATCCCA
ACCTTCCTCC
TCTGGGCACATCT
GAACTTGTTCC
233
71F
Vibrio cholerae
X76337
ATCCCACCTGGG
73
71P
TTGGGTGGC
CECT 514 T
CATATCCGGTAG
TTAACCACCTT
234
71R
CGCAAGGCCCGA
CCTCCCTAC
AGGTCCCCTGCTT
T
GTAGTTTACTA
235
72F
Yersinia pestis
AF366383
TCTGGGTTCATCC
74
72P
CTTTGCCGG
GATGGCGTGAGG
GAGCGTATTA
236
72R
CCCTAAGGTCCC
AACTCAACCC
CCACTTTGCTCTT
GGAAAGTGGC
237
73F
Arsenite-
AF406554
TCAAGACCCACG
75
73P
CCTCTGATTC
oxidizing
GCTATTAACCGT
CCATAAATGA
238
73R
bacterium
AAGCTTTTCCTCC
ACCCAACGGC
MLHE-1
CTGCTGAAAGTG
C
ACCGGATACA
239
74F
Thiomicrospira
U46506
GCCGGTGCTTATT
76
74P
CCTTCATACC
sp. CVO
CATATGCTACCGT
CCGCAATGAC
240
74R
CATTTTCTTGACA
AAGCATCACG
TATAAAAGGAG
ACGCTCCGATT
241
75F
Desulfovibrio
Z24450
GTACCGTCAGAC
77
75P
TCACAGTTC
longreachii
CATGGCTGATTA
AAGTCCAGCA
242
75R
GCACCATGGCGG
GTATCAAGGG
TTCTTCCCTCCTG
A
TGGGTTTACCT
243
76F
Bacillus
AF064705
CAAGGTACCGCC
78
76P
AACACTACG
arsenicoselenatis
CTATTTGAACGGT
TAGAGTCGAG
244
76R
ACTTGTTCTTCCC
TTACAGACCG
TAGCAACAGAGC
ATCATGAGTTC
245
77F
Uncultured
AF233412
TATTCATAAGGT
79
77P
ACATGTCCG
human fecal
ACATACAAAACA
CAATCGGAGTT
246
77R
bacterium HF74
CCACACGTGGCG
CTTCGTG
AACTTTATTCCCT
T
ATCATGAGTTC
247
78F
Uncultured
AF233408
TATTCATAAAGT
80
78P
ACATGTCCG
human fecal
ACATGCAAACGG
CAATCGGAGTT
248
78R
bacterium HF8
GTATGCATACCC
CTTCGTG
GACTTTATTCCTT
T
GCCGTCTACTC
249
79F
Uncultured
AF233413
TATTCATACGGTA
81
79P
TTGGCC
human fecal
CATACAAAAAGG
CCTGCCTCTAC
250
79R
bacterium HF10
CACACGTGCCTC
TGTACTC
ACTTTATTCCCGT
ACGGGTGCTTG
251
80F
Burkholderia
AB091761
AGGCCCGAAGGT
82
80P
CACCTGG
cepacia
CCCCCGCTTTCAT
CGACTGTATTA
252
80R
CCGTAGATCGTA
GAGCCAAGG
TGCGGTATTAATC
GTTGGCCGATG
253
81F
Burkholderia
AF148556
CGGTACCGTCAT
83
81P
GCTGATTAG
cepacia
CCCCCGACTGTAT
TCTGCCATACT
254
81R
genomovar III
TAGAGCCAAGGA
CTAGCCTGC
TTTCTTTCCGGAC
ACATGCAAGT
255
82F
OTU LT3A11,
N/A
AGCCGCAAGCTT
84
82P
CGTACGAGAG
multi-copy,
CTCTTTAGGCGG
identified as
AAATCCATTTCAC
ACACGTCATTT
256
82R
Unidentified
TCGAAAGCATAT
ATTCCTCCC
cyanobacterium
G
clone LD27
ACGAACCTTCG
257
83F
OTU LT1A53-
N/A
AGACGCGAGCTC
85
83P
GGTTAGTGG
3A9, multi-copy,
ATCCTCAGGCGA
TCAAGTACCGT
258
83R
identified as
AATTCATTTCACC
CAGATCTTC
Synechococcus
TCTCGGCATATG
sp.
G
AAAGGCCTAC
259
84F
OTU LT1A53,
N/A
CCATCGCAGTAA
86
84P
CAAGGCTTCG
multi-copy,
TGGAGTTAAGGT
GGCACTCTCTC
260
84R
identified as
CCACGCTTTGAC
GTTTCCAAG
Synechococcus
GACAGACTTAAA
sp. LBG2
AG
AAAGGCTTAC
261
85F
OTU LT3A9,
N/A
CCATCGCTGAAA
87
85P
CAAGGCATTG
multi-copy,
TGGAGTTGAGCT
CCTCCGGTTTC
262
85R
identified as
CCACGCTTTAAC
CCAGAG
Synechococcus
GACAGACTTGTA
sp. LBP1
AA
GTAACAGGTCT
263
86F
OTU TL1A7,
N/A
CGCTCTAGTAGC
88
86P
TTCGGGATG
multi-copy,
ACAAGGCCCGAA
CAAGACTTTTC
264
86R
identified as
GGTCCCCTGCTTT
GTTCCGTAC
Uncultured beta
CATCCATAGATCT
proteobacterium
clone OSlL-16
TCTTTCACCGG
265
87F
OTU TL1A9,
N/A
TCAGTGACGCAA
89
87P
AGCTTGCTC
multi-copy,
AAGCGCCTTTCA
CTCTCATCCTT
266
87R
identified as
ACTTTCTTCCATG
GTTCTTCTC
Enterococcus
CGGAAAATAGTG
gallinarum strain
T
LMG 13129
ACGGTCGCGT
267
88F
OTU LT1A31,
N/A
TCCTGAAGCGAT
90
88P
AACACGTAAG
multi-copy,
AAATCTTTAGAC
CGTCAAATTTC
268
88R
identified as
ACAAGTCGATGC
TTCCCACTC
Uncultured
CGACTCGTGACC
Crater Lake
AC
bacterium
CL500-18
ATGAAGCTACT
269
89F
OTU CL1A15,
N/A
AGGTCATCTTCA
91
89P
TCGGTAGTG
single-copy,
ACCGAAAAACTT
TGTAGGTACCG
270
89R
identified as
TCCAGCCCCGAT
TCACTTTCG
Uncultured
CATGCGATCAGA
Crater Lake
GC
bacterium CL0-
27
ATGAAGCACC
271
90F
OTU LT1A54,
N/A
TCATCTTCAACCG
92
90P
TTCGGGTGTG
multi-copy,
AAAAACTTTCCA
TGCAGGTACC
272
90R
identified as
AACCCGCGGATG
GTCACTTTCG
Uncultured
CCCGCAGGTTTC
Crater Lake
A
bacterium
CL0-64
GATCTTTGATC
273
91F
OTU LT1A55,
N/A
CAGACGCGAGCT
93
91P
TTAGTGGCG
multi-copy,
CTTCCTAAGGTG
TCAAGTACCGT
274
91R
identified as
GATAAATCCTTTT
CAGAACTTC
Uncultured
ACCTCTCGGCGT
freshwater
A
bacterium
LCK-26
AACGTACCCA
275
92F
OTU CL1A9,
N/A
GGCCGCTCCAGG
94
92P
AGAGTGGG
multi-copy,
AGCACGAGGTCT
AAGGATATTA
276
92R
identified as
TGCGATCCCCCG
GCCTCTACCG
Zoogloea
CTTTCATCCTTAG
ramigera
A
TGAAGTTCCTT
277
93F
OTU LT1A27,
N/A
ATCTTTCATCAAA
95
93P
CGGGAATGG
multi-copy,
ATTTTTTCCCGGC
TTCTTCCCTAC
278
93R
identified as
TCGGCGATGCCG
TGAAAGAGG
Uncultured
CCAAGACGGAGT
actinomycete
clone SFD1-39
CTCATCAGCAA
279
94F
OTU LT1A46,
N/A
TCATGTAAGCCG
96
94P
TGGTGGGAG
multi-copy,
CTCCTCCGGCGG
TCAACTCCGGA
280
94R
identified as
AATCACACCTTTG
GGAGAACC
Uncultured
CTCCGCAGAGTT
planctomycete
C
clone CY0ARA-
031E04
GGCAGCACGG
281
95F
OTU TL1A1,
N/A
TATTCTTAAAGCG
97
95P
TCTAGTTTAC
multi-copy,
CCAGGCCTTGCG
TCAAATCCTCC
282
95R
unidentified
GTCCCCAGCTTTT
TCCCCACTG
CTCCTCAGAGAT
GTCAGACTTCG
283
96F
OTU TL1A2,
N/A
CTCCATCAGCGC
98
96P
GTCTGATTG
multi-copy,
CCTTGCGAGCTTT
GGTACTTCTTC
284
96R
unidentified
CATCCCTTCTGCG
CCGAGCAAC
ACGAAGGGATCG
ATGTAGCAAT
285
97F
OTU TL1A6,
N/A
GGGGCACGGGCT
99
97P
ACAGGACAGC
single-copy,
CATCTTGGGGCG
CGTACATTTGA
286
97R
unidentified
GAATCACACCTTT
TTCCCTACG
GGTCCGCAAACA
T
ATGAAGCTGG
287
98F
OTU CL1A2,
N/A
TCCTTGACCAAA
100
98P
AGCTTGCTCC
multi-copy,
ATTCTTTCCACGC
GCGAGCTCATC
288
98R
unidentified
CCGTGGGATGCC
CTTGACC
CCAAGGCGTCGT
A
ACGGGAGCAA
289
99F
OTU CL1A10,
N/A
TGATATCGGCCG
101
99P
TCCTGGTG
multi-copy,
CTCCAATCGCGC
CCACTGTATTA
290
99R
unidentified
GAGGTCTTGCGA
GAGCAGACC
TCCCCCGCTTTCA
T
ACGGCTTCGGC
291
100F
OTU LT2A3,
N/A
GCTCTTGCGAGCT
102
100P
CTAGTAAAG
multi-copy,
CCCTTTCCCGAAA
AGGGCTGTTCA
292
100R
unidentified
AACTCCTTACGA
CCCTAATGG
GTTCCGTCGCTC
TTAACTTAAGT
293
101F
OTU LT2A12,
N/A
AGACGCGAGCTT
103
101P
GGCGGACGG
multi-copy,
CTCTTTAGGCGG
GGTACACGTC
294
101R
unidentified
ATTACTCCATTTC
GTTTTATTCC
ACTCGGAAGCAT
A
TAACGCGGGG
295
102F
OTU LT2A16,
N/A
CGCTCCAATAGC
104
102P
CAACCTGG
multi-copy,
GAGAGGTCTTGC
GGGTATTAGCC
296
102R
unidentified
GATCCCCCCCTTT
CAGAGCG
CACCCGAAGGTC
G
AGAGTTTGATC
297
103F1
OTU LT1A15,
N/A
CGGTCCCAGCGTT
105
103P
CTGGCTCAG
298
103F2
single-copy,
TCCAGTAATCTCT
ACGGAGGTAG
unidentified
CTCTAGACTACTG
CAATACCTTA
CTTACGACGTA
GTGCTTCTTCT
299
103R
TCCGGTACC
TTCGGTTATGT
300
104F
OTU LT1A16,
N/A
TAATCCTAAAGC
106
104P
TGATGGCGA
multi-copy,
GCCAGGCCTTGC
TCGGGTAACGT
301
104R
unidentified
GGTCCCCAGCTTT
CAATAAACC
CCTCCTAAGAGA
T
AACCCCGGTG
302
105F1
OTU LTIA18,
N/A
GTCCCCCGCTTTC
107
105P
GCGAGTGG
303
105F2
multi-copy,
ATCCATAGATCG
AACCCTGGTG
unidentified
TATGCGGTATTA
GCGAGTGG
GCGTAACTTTCGC
TTCTTACGGTA
304
105R
CCGTCATG
GAGCGATGAA
305
106F
OTU LT3A1,
N/A
CAATATTCGGTAT
108
106P
GTTTCTTCGG
single-copy,
TAGCACCGGTTTC
AGCCGGTGCTT
306
106R
unidentified
CCGGTGTTATCCC
CTTTTGTAG
AAAGTGGAGGG
GGTAACAGGT
307
107F
OTU LT3A2,
N/A
AGGTCTTGCGAT
109
107P
TAAGCTGACG
multi-copy,
CCCCCCCTTTCAC
CAGAGTATTA
308
107R
unidentified
CCGTAGGTCGTA
ATCCGAAGCG
TGCGGTATTAATC
GGTCTAGTTTA
309
108F
OTU LT3A7,
N/A
CAGCTTTTCTCCT
110
108P
CTAGATGGG
multi-copy,
CAGAGATTACGC
TTCTTCTGTGG
310
108R
unidentified
GGTATTAGCCTG
GTAACGTCC
AGTTTCCCCAGGT
CATCGGAACG
311
109F
OTU LT1A35,
N/A
CTTTCCCCCTCAG
111
109P
TACCTTATCG
multi-copy,
GGCGTATGCGGT
CGCAGTCTGTG
312
109R
unidentified
ATTAGCGCAACT
TTAGAGCTG
TTCGCTGCGTTAT
CGTGAGAATCT
313
110F
OTU LT1A55,
N/A
CAGACGCGAGCT
112
110P
ACCCTTAGG
multi-copy,
CTTCCTAAGGTG
GCTTGCATCCT
314
110R
unidentified
GATAGATCCTTTT
CTGTATTAC
ACCTCTCGGCAT
A
TGTCGTCAGCT
315
111F
Control 1372
N/A
TGACGGGCGGTG
113
111P
CGTGTCG
TGTACAAGGCCC
AAGGAGGTGA
316
111R
G
TCCAGCCG
The PCR products in each reaction mixture (e.g., 16S rDNA and 18S rDNA) may be generated from dNTPs which contain a mixture of dATP, dGTP, dCTP, dTTP, and amino allyl-dUTP. The labeling step may employ dye incorporation resulting from a coupling reaction between a cyanine (Cy) and the PCR product. The pools of labeled PCR products may be hybridized with the array, whose immobilized oligonucleotides specify 50-mer sequences that are complementary to at least some of the individual rDNA sequences amplified from each sample. In some cases, the experiment may be replicated by performing a second “dye swap” experiment to minimize any false signals due to differential incorporation of the dye in the amplification products.
Also, probes that target taxa at different hierarchical levels may be included in the array in order to optimize detection of desired bioindicator organisms. For example, in addition to developing PCR primers that are specific to a single species, primers that are capable of detecting several species in a particular genus may be developed (e.g., Oldach, D. W., et al., 2000, Proc. Natl Acad. Sci. U.S.A. 97:4303–4308). The more generic primers may be used both as a confirmation that a particular genus is present in any sample that tested positive with the more specific primers, and as an indicator that potentially unknown or undetected members of the genus are also present.
The array may provide a qualitative result and/or a quantitative result. For example, as shown in
The array may also be used as a quantitative assessment tool, to monitor the change in various microbes over time, or to monitor the relative amounts of a microbe between two samples that vary in location (e.g., for two different bodies of water, or two locations in one body of water) or time of sampling (e.g., a single body of water sampled at two different seasons). Referring now to
As described herein, the array may also be used to determine how chemical additions to water (e.g. cadmium, atrazine, perchlorate) may change the microbial community, and/or to detect known water pathogens. For example, the microarray may include 16S rDNA sequences from several known pathogens.
In one embodiment, an array of oligonucleotides that are isolated from known and unknown OTUs may be prepared. As used herein, known OTUs comprise sequences that are ≧97.5% identical to sequences that have been reported in public databases, whereas unknown OTUs comprise sequences that do not meet this criterion and are believed to represent as yet unknown organisms.
Such taxon-specific arrays may be used to detect microbes that are known to be characteristic of a particular type of water system. For example, in one embodiment, the array may be formulated to detect microbes common to fresh water systems. Or, the array may be formulated to detect microbes common to marshlands or small tidal pools. Or, arrays having nucleic acids derived from estuary water samples may be used to analyze water from various estuaries. The development of an array that utilizes freshwater nucleotide sequences is described in the Examples, below.
Sample collection and DNA extraction. To develop probes for an array, three lakes were sampled: Lake Townsend (LT) (Greensboro, N.C.); City Lake (CL) (High Point, N.C.); and Toolik Lake (T L) (Alaska). Lake Townsend and City Lake are temperate mesotrophic and eutrophic municipal drinking water reservoirs, respectively. Toolik Lake is a highly oligotrophic, glacial lake located in the Arctic Long Term Ecological Research Site above the Arctic Circle in Alaska (Moon-van der Staay, S. Y., et al., 2001, Nature, 409:607–610).
Five samples of surface water were collected: (1) LT-1J—at an open water location in Lake Townsend (station 1), depth=8.3 m, on Jun. 14, 2000; (2) LT-2J—at a shallow, near shore location in Lake Townsend (station 2), depth=1.3 m, on Jun. 14, 2000; (3) LT-1M—at station 1 of Lake Townsend, on Mar. 28, 2001; (4) CL—at an artificially aerated location in City Lake near a subsurface water treatment system intake on May 22, 2001; and (5) TL—at a location near the main LTER sampling station in Toolik Lake on Aug. 11, 2000. Each sample (˜100 ml) was drawn through GF/C and GF/F glass fiber filters that were placed in cetyltrimethylammonium bromide (CTAB) buffer for storage at room temperature until later DNA extraction. Other lake samples, such as water samples from lakes that may be diagnostic of deformities found in members of the ecosystem may be used. For example, tests have been conducted using a group of North Dakota lakes that were paired according to geographical proximity. Each pair of lakes includes one lake that has been associated with a high level of frog deformities and one lake that has not been associated with any known deformities in frogs or any other organism. Samples from the lakes were used to isolate DNA for array analysis to ascertain microbial bioindicators associated with conditions leading to such deformities.
Genomic DNA was extracted from each water sample using a CTAB (cetyltrimethylammonium bromide) buffer DNA isolation technique (Rublee, P. A., et al., 1999, Va. J Sci., 50:325–335). Briefly, the glass fiber filter was macerated in 2 ml CTAB in a 15 ml polypropylene conical tube using a sterile wooden applicator stick. After heating for 1 hr at 65° C., the mixture was extracted with 2 ml 24:1 (v/v) chloroform-isoamyl alcohol, and the DNA isolated from the aqueous portion by precipitation with 0.7 volumes 100% 2-propanol. The precipitate was pelleted, air-dried, and the DNA rehydrated in 25 μl TE buffer (pH 7.4) and stored at −20° C.
PCR amplification of genomic DNA from water samples for cloning rDNAs. SSU rDNA was amplified by PCR using prokaryotic-specific and eukaryotic-specific forward and reverse primers in 50 μl reactions (Table 1). Using the appropriate primer pairs, separate reactions were prepared for 16S rDNA and 18S rDNA. The amplification reactions consisted of: 5 μl 10× PCR Buffer; 5 μl Promega 25 mM MgCl2; 5 μl 100 mM BSA; 2.5 μl 16 mM dNTP stock (4 mM each of dATP, dCTP, dGTP and dTTP); 1 μl each of 10 μM forward and reverse primers; 1 U Taq DNA Polymerase; 30.2 μl sterile deionized H2O; and 1 μl genomic DNA. An MJ Research PTC-100 Programmable Thermal Controller was used to amplify samples under the following conditions: 2 min initial denaturation at 94° C.; 30 cycles of 1 min denaturation at 94° C.; 1 min annealing at 56° C. for 16S primers or 58° C. for 18S primers; and 2 min extension at 72° C.; 5 min final extension at 72° C. PCR products were verified by gel electrophoresis.
Cloning and sequencing of amplified PCR products. Purified PCR products were subcloned in plasmid vectors using the Invitrogen TOPO TA Cloning Kit according to the manufacturer's protocol. Ligation reaction mixtures were then used to transform TOP10 Chemically Competent E. coli cells and recombinant plasmids were identified by growth of bacterial colonies on LB agar plates containing 50 μg/ml ampicillin. Individual colonies from each plating were inoculated into LB liquid medium containing 50 μg/ml ampicillin and grown overnight with antibiotic selection. Inserts were purified from cultures using a QIAGEN QIAprep Spin Miniprep Kit according to the manufacturer's protocol. After removal of the insert, gel electrophoresis was used to verify the presence of a DNA fragment corresponding in size to 16S rDNA or 18S rDNA.
Fifty verified clones from each library were sequenced using a LI-COR Global Edition IR2 System for automated DNA sequencing. Sequencing reactions were prepared using an Epicentre Technologies SequiTherm EXCEL™ II DNA Sequencing Kit-LC (for 25–41 cm gels) according to the Cycle Sequencing Protocol provided. Sequencing reactions included: 3.5× SequiTherm EXCEL™ II Sequencing Buffer; fluorescent (IR)-labeled M13–20 forward and reverse primers; purified cloned 16S rDNA or 18S rDNA; sterile deionized H2O; SequiTherm EXCEL II DNA Polymerase; and SequiTherm EXCEL II-LC Termination Mixes A, C, G and T (each containing dATP, dCTP, dTTP, 7-deaza-dGTP, and one ddNTP). Using an MJ Research PTC-100 Programmable Thermal Controller, reactions were amplified by PCR using the following conditions: 4.5 min initial denaturation at 95° C., followed by 30 cycles of 30 sec denaturation at 95° C., 30 sec annealing at 51° C., and 1 min extension at 70° C. After amplification, Stop/Loading Buffer was added to reaction products, which were denatured for 5 min at 95° C. and loaded into a 41 cm polyacrylamide gel. During electrophoresis of reaction products, dual 700 and 800 nm detection channels were used for simultaneous bidirectional sequencing of each clone and sequence read lengths were at least 550 bp in each direction.
Sequence Alignments and Community Analyses. It is generally accepted in the art that 1000 nucleotides of sequence information is sufficient for even a detailed phylogenetic analysis (Oldach, D. W., et al., 2000, Proc. Natl Acad. Sci., U.S.A. 97:4303–4308). Thus, partial sequences were obtained for each clone and the first 500 nucleotides from both 5′ and 3′ ends. The use of 1000 nucleotides for phylogenetic ordering of the sequences was subsequently verified by generating complete sequences for 18S rDNA clones, with no improvement in the data (results not shown). After checking each sequence for the presence of chimeric properties using the program CHIMERA_CHECK (version 2.7; Ribosomal Database Project II, Center for Microbial Ecology, Michigan State University, available on-line), one sequence was excluded. The remaining sequences were submitted to the National Center for Biotechnology Information website for BLAST analysis (Altschul, S. F., et al., 1990, J. Mol. Biol., 215:403–410).
Sequence alignments and analyses were performed using the BioEdit Sequence Alignment Editor and Analysis software (version 5.0.9; Department of Microbiology, North Carolina State University, available on-line), which includes CLUSTAL W as an accessory application for multiple alignments. Libraries were compared in pairwise fashion by combining and aligning two libraries at a time (100 sequences of 16S rDNA or 18S rDNA). Libraries were also merged into one group for alignment and comparison (249 16S rDNA sequences or 250 18S rDNA sequences).
Taxonomic classifications were based on identity matrices generated using an analysis tool incorporated into BioEdit. Sequences having identity scores of 0.975 or greater were considered to be sufficiently similar to group them into the same operational taxonomic unit (OTU). After grouping clones into OTUs, several diversity indices were calculated for each library. These included: (1) species richness, or total number of OTUs; (2) Simpson's dominance index, used to describe the distribution of clones among OTUs, or evenness; and (3) the Shannon-Wiener index, which serves as a statistical measure of the probability of correctly guessing the OTU identity of a randomly selected clone (Colinvaux, P. 1993. Ecology 2. John Wiley & Sons, Inc., New York, U.S.A). In addition, Sorensen coefficients (Lemke, M. J., et al., 1997, Microb. Ecol., 34:224–231) were calculated to measure the similarity in species composition between two communities, or the proportion of OTUs shared between two libraries.
Also estimated was total species richness (S) using four methods based on the distribution of OTUs within a library. These included: Scov, an estimate based on “coverage” (Finlay, B. J., 2002, Science, 296:1061–1063; Giovannoni, S. J., et al., 1990, Nature, 345:60–63); Smax, an estimate based on rarefaction analysis (Haldeman, D. L., et al, 1994, Appl. Environ. Microbiol., 60:2697–2703; Methe, B. A., and J. P. Zehr, 1999, Hydrobiologia, 401 :77–96), which was performed using the program Analytic Rarefaction (version 1.3; Stratigraphy Lab, University of Georgia, available on-line); and SACE and SChao 1, two estimates that were evaluated using a form processor and spreadsheet available through a web-based interface (ASLO, Limnology and Oceanography Methods, available on-line).
Phylogenetic analyses were conducted to assess molecular evolutionary relationships using MEGA software (version 2.1; Molecular Evolutionary Genetics Analysis, available on-line). All phylogenetic analyses are sensitive to alignment methods, assumptions regarding mutational rates, and the types and amount of sequence data used (Troesch, A., et al., 1999, J. Clin. Microbiol., 37:49–55.). Trees were constructed using the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) and distances were estimated according to the Kimura 2-parameter model for nucleotide exchange with a transition/transversion ratio of 2.0 (Hurlbert, S. H., 1971, Ecology 52:577–586).
Real-time Quantitative PCR. Real-time Quantitative PCR (Q-PCR) experiments were designed to analyze the relative abundance of two 16S rDNA OTUs and one 18S rDNA OTU in three different samples using a Cepheid Smart Cycler system. The presence and accumulation of fluorescence bound to each target OTU was measured directly and compared among LT-1J, LT-1M and CL. Individual 25 μl reactions included: 2.5 μl Takara 10× Ex Taq Buffer; 1.25 μl Takara dNTP Mixture (2.5 mM each); 1.25 μl SYBR® Green I nucleic acid gel stain (10×); 0.25 μl Takara Ex Taq™; 1 μl OTU-specific forward and reverse primers (10 μM each); 16.75 μl sterile deionized H2O; and 1 μl experimental template (genomic DNA sample —0.025 μg/μl), positive control (mixed clone standard—25 pg/μl each), or negative control (sterile deionized H2O). The mixed clone standard was prepared by combining three clones representing three experimental samples used in the experiment (i.e., genomic DNA samples from three different OTUs). Relative abundance estimates were calculated using a 1:10 dilution series of the mixed clone standard to determine cycle number differences between 25 pg, 2.5 pg, 0.25 pg, and 0.025 pg template concentrations.
Multiplex PCR of probes for array. To generate the target sequences used for hybridization to the array, a multiplex PCR amplification using at least 45 primer pairs developed from an analysis of individual OTUs, may be performed. The sequences of the eukaryotic primers and associated 50-mer probes are shown in Table 2. The sequences of the prokaryotic primers and associated 50-mer probes are shown in Table 3.
The conditions for multiplex PCR are as follows. Multiplexed PCR reactions containing ˜250 ng genomic DNA are prepared in 0.5 ml thin-walled microcentrifuge tubes. The final reaction volume is 50 μl and contains a 200 nM final concentration of each primer, 5 μl 10× buffer, 5 μl BSA, 5 μl dNTPs, 1.25 U Taq, and sd H2O (remaining volume). Reactions are placed in a programmable thermal controller and DNA amplification by PCR is carried out under the following conditions: initial denaturation at 94° C. for 2 minutes; 30 cycles of denaturation at 94° C. for 1 minute, annealing at 1 to 3 degrees below lowest primer Tm, extension at 72° C. for 1 minute; final extension at 72° C. for 1 minute; and storage at 4° C. of reaction product until use. The dNTP mixture is prepared by adding 16.6 μl sd H2O to 2 μl 50× dNTP stock solution for an 8.33-fold dilution, where 50× dNTP stock solution is 10 μl each 100 mM dATP, dGTP, dCTP; 8 μl 100 mM amino allyl-dUTP; and 2 μl 100 mM dTTP.
The PCR products may, in some cases, be labeled using fluorescent dyes. The PCR product is transferred to a 1.5 ml microcentrifuge tube and 5 μl 3 M sodium acetate and 500 μl 100% ethanol are added. The contents are thoroughly mixed and stored overnight at −70° C. The samples are removed from −70° C. storage and spun in a microcentrifuge at 14,000 rpm for 20 minutes. After pouring off the supernatant, 500 μl 70% ethanol is added to wash the DNA pellet and this mixture is microcentrifuged at 14,000 rpm for 10 minutes. The supernatant is again poured off, the tube is allowed to air dry to remove all ethanol, and the pellet is then resuspended in 15 μl nuclease-free H2O. The Cy dyes are removed from −20° C. storage and resuspended in 15 μl 0.1 M sodium bicarbonate, pH 9.0. The Cy dye and DNA resuspensions are combined, mixed well, and allowed to incubate for 1 hr at room temperature in the dark. To quench any unbound Cy dye after the dye coupling reaction, 15 μl 4 M hydroxylamine are added to each sample and these are incubated for 15 minutes at room temperature in the dark. Labeled samples are then purified using a PCR purification kit according to the manufacturer's protocol.
Spotting of oligonucleotides on the array. To immobilize nucleic acids on the array the following protocol was used. Each 50-mer oligonucleotide to be used as a probe sequence (i.e., sequences corresponding to SEQ ID NOS: 5–113 or the complement of these sequences) on the array is diluted 1:10 with 3×SSC/0.1% sarkosyl in a 96-well microplate for a final oligonucleotide concentration of ˜250 ng/μl. Epoxy-coated slides are secured in slide positions of arrayer for printing. After the oligonucleotides are printed, the slides are UV cross-linked at 60 mJoules, baked at 80° C. in an oven for 2 hours, and stored at room temperature. The 3×SSC is prepared using a 20×SSC concentrate containing 3 M NaCl and 0.3 M sodium citrate, pH 7.0.
Hybridization of DNA sample to array. After purification, the Cy3 and Cy5-labeled sample eluates may be combined and lyophilized until almost dry, leaving approximately 5–10 μl behind. The sample may be resuspended using 80 μl Roche DIG Easy Hyb hybridization buffer and a clean lifterslip is placed on the microarray being used. The sample is heated at 95° C. for 2 minutes, cooled on ice for 1 minute, spun down to collect any condensation, and pipetted under the lifterslip. Next, the microarray is sealed within a hybridization cassette using the cassette lid and placed into a 45–55° C. water bath overnight. The next morning, three wash solutions are heated to 37° C., the hybridization cassette is removed from the water bath, and the microarray is removed from the cassette. The microarray with lifterslip is gently dipped into a staining dish containing wash buffer #1 (1×SSC, 0.1% SDS), to release the lifterslip. The microarray is then placed in a staining dish cassette and gently washed in wash buffer #1 for 5 minutes. Using the same technique, the microarray is next washed in wash buffer #2 (1×SSC), for 5 minutes. Finally, the microarray is washed in wash buffer #3 (0.05×SSC), by gently dipping it 5–10 times. The microarray is removed from the staining dish cassette and tapped on edge against the benchtop to remove all solution droplets. Once dry, the microarray is scanned.
Analysis of Clones. Approximately 50 prokaryotic rDNA and 50 eukaryotic rDNA clones for each of the five lake samples (500 rDNA sequences) were sequenced through a 1700 bp segment of the eukaryotic 18S rDNA, or a 1540 bp segment of the prokaryotic 16S rDNA, to provide for phylogenetic classification of known and novel species (Pace et al., 1986, Adv. Microb. Ecol., 9:1–55; Sogin and Gunderson, 1987, Annals. NY Acad. Sci., 503:125–139). Based on the rDNA sequencing alignments, a level of 97.5% sequence identity was the criterion by which rDNAs were placed in the same operational taxonomic unit (OTU). Because multiple small subunit rDNA copies may reside within a species genome (Farrelly et al., 1995, Appl. Environ. Microbiol., 61:2798–2801), a 97.5% level of sequence identity allows for the possibility that a different sequence in the same species was recovered. A software program (CHIMERA-CHECK; Kopzcysnski et al., 1994, Appl. Environ. Microbiol., 60:746–748; Wang and Wang, 1995, Appl. Environ. Microbiol., 63:4645–4650; Qui et al, 2001, App. Environ. Microbiol., 58:2717–2722) was also employed to reduce the possibility of misidentifying a chimeric rDNA as an unique clone.
For each sample, libraries of SSU rDNA clones were produced, individual clones were sampled, sequences for each clone were generated, and standard diversity statistics were computed (Table 4). Based on a comparative analysis of all prokaryotic (16S) rDNA sequences, it was determined that 49 OTUs contained multiple sequences and that 62 OTUs were unique, each containing a single sequence. An analysis of all eukaryotic (18S) sequences resulted in 42 OTUs containing multiple sequences and 67 unique OTUs.
TABLE 4
Comparison of prokaryotic and eukaryotic diversity
LT-1J
LT-2J
LT-1M
CL
TL
rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S
Number of clones
50
50
50
50
50
50
49
50
50
50
Number of OTUs
33
31
31
32
26
34
28
28
23
12
Evenness
0.039
0.049
0.050
0.053
0.089
0.043
0.079
0.102
0.078
0.358
Shannon-Wiener
3.38
3.24
3.24
3.24
2.84
3.35
3.00
2.90
2.86
1.62
index
LT-1J: Lake Townsend, station 1, June;
LT-2J: Lake Townsend, station 2, June;
LT-1M: Lake Townsend, station 1, March;
CL: City Lake;
TL: Toolik Lake.
Species Diversity Measures. Prokaryotic and eukaryotic species richness, evenness, and the Shannon-Wiener index differed among lakes. In general, Lake Townsend, NC, contained more species and showed the most even distribution of species; consequently, its Shannon-Wiener index values were the highest. In contrast, Toolik Lake, AK, had the lowest richness estimates, especially for eukaryotes, indicating that species diversity was much lower here than in the temperate lakes and that a few successful competitors dominated the arctic community.
As a first indication of diversity, various statistical measurements of the recovered sequences were made to determine the species coverage, species evenness (Simpson's Index of Dominance; Colinvaux, 1993, Ecology 2, John Wiley & Sons, Inc. New York, N.Y.), species richness (the number of recovered species in a sample), species diversity (Shannon-Wiener index; Nubel et al., 1999, Appl. Environ. Microbiol., 65:422–430) and the estimated proportion of shared OTUs between samples (Sorenson similarity coefficient; Lincoln et al, 1998, A Dictionary of Ecology, Evolution, and Systematics, Cambridge University Press, New York, N.Y.; McCaig et al., 1999, Appl. Environ. Microbiol., 65:1721–1730). Coverage estimates of the percentage of OTUs recovered from a source were based on the relative abundance of the clones already obtained, and indicated that 48 to 76% of the prokaryotic rDNAs, and between 48 and 90% of the eukaryotic rDNAs, had been recovered from the samples. The highest coverage (i.e., 90%) was for Toolik Lake; apparently caused by the high level of recovery of a single rDNA. Not unexpectedly, the species evenness and richness was about the same for all the North Carolina lake samples, but the distribution of recovered species was much more skewed and lower in Toolik Lake, Alaska. To generate a nucleic acid array for monitoring water, however, the purpose of the census is not necessarily to identify all the microbial species that exist in these samples, but rather to survey water sources for relatively common microbes whose appearance and abundance can be monitored on a microarray platform.
Rank-abundance curves (
TABLE 5
Estimates of species richness (S) for each prokaryotic and eukaryotic community
LT-1J
LT-2J
LT-1M
CL
TL
rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S
Number of OTUs
33
31
31
32
26
34
28
28
23
12
Scov
57
56
54
62
44
71
46
47
29
14
Smax
93
72
73
74
40
93
53
47
40
12
SACE
61
80
77
110
110
106
67
65
38
17
SChaol
54
77
63
88
91
99
54
60
28
14
LT-1J: Lake Townsend, station 1, June;
LT-2J: Lake Townsend, station 2, June;
LT-1M: Lake Townsend, station 1, March;
CL: City Lake;
TL: Toolik Lake.
Sequence Identifications and Library Comparisons. Clone sequences were submitted for BLAST analysis to assess phylogenetic affiliations with reported sequences in the GenBank database. Sequence alignments having ≧97.5% identity were used to propose OTU identifications and determine the proportion of known OTUs for each library (Table 6). The Lake Townsend March sample contained the lowest average proportion of known OTUs (24.8%), while Toolik Lake had the highest (43.0%). Identifications for clones within the same OTU were consistent, suggesting that a 97.5% identity threshold grouped individuals at the species level.
TABLE 6
Summary of prokaryotic and eukaryotic OTUs
LT-1J
LT-2J
LT-IM
CL
TL
rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S
No. known clones
21
17
16
21
21
19
31
20
25
32
Proportion known
12/33
8/31
10/31
8/32
6/26
9/34
13/28
6/28
14/23
3/12
OTUs (%)
(36.4)
(25.8)
(32.3)
(25.0)
(23.1)
(26.5)
(46.4)
(21.4)
(60.9)
(25.0)
LT-1J: Lake Townsend, station 1, June;
LT-2J: Lake Townsend, station 2, June;
LT-1M: Lake Townsend, station 1, March;
CL: City Lake;
TL: Toolik Lake.
Number of known OTUs = number of OTUs with clones having ≧97.5% sequence similarity to GenBank entries. Known clones refer to clones whose sequences correspond to known microbial species or unidentified species in the GenBank database.
Samples having similar estimates of species diversity were distinguished by differences in community composition. For instance, 8 eukaryotic OTUs were identified in each Lake Townsend sample, but the species composition of this group varied between samples. Comparing only the OTUs with multiple sequences, the following observations were made: LT-1J species included Chilomonas paramecium, Cryptomonas ovata, and Geminigera cryophila; LT-2J species included Brachionus plicatilis, Cryptomonas ovata, Didinium nasutum, and Dileptus sp., and the LT-1M species included Cryptomonas ovata and Tabularia tabulata. A comparison of the unique OTUs distinguished these samples even more.
Based on sequence alignments and comparisons that included all OTUs, phylogenetic trees were generated according to the UPGMA method to show the overall distribution of OTUs among the five samples. The prokaryote tree in
To determine which OTUs, if any, appeared in more than one library, the sequences from each library were compared to those in every other library in pairwise library comparisons and a similarity coefficient was calculated for each pairing (Table 7). Although no prokaryotic sequences were shared between LT-2J and TL, there was some overlap between every pair of samples and the degree of overlap varied considerably. In some comparisons, roughly equal proportions of prokaryotic and eukaryotic OTUs were shared, but other comparisons revealed different patterns.
TABLE 7
Sorensen coefficients for prokaryotic and eukaryotic sample comparisons
LT-1J
LT-2J
LT-1M
CL
TL
rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S
LT-1J
1
1
0.344
0.159
0.169
0.215
0.230
0.068
0.071
0.093
(11)
(5)
(5)
(7)
(7)
(2)
(2)
(2)
LT-2J
1
1
0.070
0.061
0.169
0.133
0
0.091
(2)
(2)
(5)
(4)
(2)
LT-1M
1
1
0.074
0.161
0.122
0.174
(2)
(5)
(3)
(4)
CL
1
1
0.039
0.200
(1)
(4)
TL
1
1
Coefficients were calculated as follows: S = 2 × C/(A + B), where A and B represent the numbers of OTUs in libraries A and B, respectively, and C represents the number of OTUs shared by A and B (34, 40). ( ) indicate the number of OTUs that were shared by the paired libraries. LT-1J: Lake Townsend, station 1, June; LT-2J: Lake Townsend, station 2, June; LT-1M: Lake Townsend, station 1, March; CL: City Lake; TL: Toolik Lake.
Venn diagrams depict sample comparisons at different spatial and temporal scales (
Thus, it was found that for the five lake samples analyzed, 26 different eukaryotic OTUs were represented by multiple copies, including 11 that are associated with known species. Another 79 eukaryotic OTUs were obtained as single copy clones and almost all of these represent unidentified species (Marshall, 2002, Masters Thesis, University of North Carolina at Greensboro). Similarly, 45 different prokaryotic OTUs were found in multiple copies among the collection of samples, of which 10 are associated with a known species, and another 19 resemble reported sequences for as yet unidentified species. Another 92 single copy rDNA sequences, most from unidentified prokaryotes, were recovered from the samples (Amos, 2002, Masters Thesis, University of North Carolina at Greensboro). Both known and unidentified rDNA sequences may be used as probes printed on the assay matrix of the present invention.
The ability to assess environmental parameters of water quality may require a sufficient number of potential bioindicator species, but may also require sequences having sufficient similarity across samples to allow for some general application. As noted in Table 8, a diversity of microbial species may be readily retrievable from a single body of water for even an oligotrophic source such as Toolik Lake, Alaska. While every sample produced several unique OTUs, all of the lakes produced multiply represented OTUs, and the most common OTU in each sample accounted for 10% or more of all the rDNAs analyzed in each of the samples.
TABLE 8
Relative abundance of eukaryotic and prokaryotic OTUs
Most abundant
OTU
2X OTUs
1X OTUs
Total OTUs
Eukary.
Prokary.
Eukary.
Prokary.
Eukary.
Prokary.
Eukary.
Prokary.
LT-1J
10%
8%
9
10
23
26
32
36
LT-2J
14%
10%
9
8
22
26
31
34
LT-1M
10%
14%
8
7
26
23
34
30
CL
14%
22%
10
9
21
22
31
31
TL
58%
20%
7
12
5
12
12
24
LT-1J; Townsend, NC; June, Station 1;
LT-2J; Townsend, NC; June, Station 2;
LT-1M, Townsend, NC; March, Station 1;
CL, City Lake, NC May;
TL, Toolik Lake, AK;
August. 2× represents OTUs with at least 2 members; 1× represents OTUs with only one member.
Table 9 shows the pattern of shared and unshared OTUs among the five freshwater lake samples. Unshared OTUs refer to rDNA sequences that were recovered and characterized only in the designated sample either as a single copy, referred to as a unique OTU, or in multiple copies. It can be seen that the distribution of some OTUs is broad, while for others it is more localized (Table 9), suggesting that many microbial species exist across a range of watersheds and that a general purpose DNA microarray, that may be used for multiple watersheds, may be developed. An example analysis of specific OTUs is shown in Table 10.
A preliminary analysis of rDNA sequences from paired North Dakota lake samples (where one lake sample that exhibits substantial deformities in the frog population and one lake sample does not) acquired from the Fargo, N. Dak. USDA station indicates that some of the OTUs for unknown species are shared with sequences found in North Carolina lakes. Moreover, preliminary real-time PCR experiments suggest that at least some microbes exist an endemic level in almost all freshwater lakes, suggesting that that relative abundance for these endemic microbes is primarily dictated by local water conditions.
TABLE 9
Shared and unshared OTUs among the five freshwater lake samples
A
B
C
D
E
Euk.
Prok.
Euk.
Prok.
Euk.
Prok.
Euk.
Prok.
Euky.
Prok.
Unshared
18
22
19
19
19
19
18
20
5
12
OTUs
OTUs in 2
2
5
1
4
3
8
2
4
2
19
samples only
Toolik only
0
0
0
0
0
0
0
0
—
—
Townsend
5
6
3
6
5
2
—
—
—
—
only
Townsend or
2
2
1
3
2
1
5
6
—
—
City
All lakes*
4
0
3
0
5
0
5
0
5
0
*All lakes does not necessarily mean all samples.
A: Townsend, NC, June, Station 1;
B: Townsend, NC, June, Station 2;
C: Townsend, NC, March, Station 1;
D: City Lake, NC, May;
E, Toolik Lake, AK, August
Euk = Eukaryotic;
Prok = Prokaryotic
TABLE 10
Relative abundance of five eukaryotic rDNA species found in all three
sampled lakes
A
B
C
D
E
Cryptomonas
30%
12%
20%
30%
8%
ovata
Unidentified
0%
0%
10%
6%
58%
18s rDNA-1
Ochromonas
12%
6%
6%
8%
4%
tuberculata
Oxytricha
2%
10%
2%
8%
10%
longa
Unidentified
10%
0%
4%
2%
10%
18s rDNA-2
A: Townsend, NC, June, Station 1;
B: Townsend, NC, June, Station 2;
C: Townsend, NC, March, Station 1;
D: City Lake, NC, May,
E: Toolik Lake, AK, August
Library Screening vs. Real-time Q-PCR. Several OTUs may be found at quantitatively different levels in different ecosystems. Three OTUs that appeared to be recovered differentially from one water sample were used in fluorescence detection real-time PCR experiments to determine if they were also present in other water samples (
The relative abundance of each OTU was compared and estimated across the same three samples based on a dilution series of a known standard (data not shown). According to cycle threshold differences between growth curves in
Real-time PCR assays also allowed for an estimation of the sensitivity of rDNA amplification for detecting community members. Based on four completed E. coli genomes from GenBank entries AE014075 (Venter, J. C., et al., 2004, Science, 304:66–74), U00096 (Blattner, F. R., et al., 1997, Science, 277:1453–1474), BA000007 (Lincoln, R., G. Boxshall, and P. Clark, 1998, A Dictionary of Ecology, Evolution and Systematics. Cambridge University Press, New York, N.Y.), and AE005174 (Pace, N. R., et al., 1986, Adv. Microb. Ecol., 9:1–55), it was estimated that 16S rDNA makes up about 0.206% of the E. coli genome, and therefore, about 52 pg of 16S rDNA should be present in 25 ng of genomic DNA material. Experiments indicated that Q-PCR detected a specific rDNA signal from as little as 3.6×10−3 pg of genomic DNA, based on a comparison with the Q-PCR signal evoked by individual rDNA clones, indicating that clones occurring at a frequency as low as 6.9×10−5 should be detectable by Q-PCR, and that a sampling of 14.5×103 clones would be required for a mean recovery of one target clone. Assuming a Poisson distribution of clones in a library, it was estimated that to ensure the recovery of any one clone at a probability of greater than 99%, a library screening method would require 66.7×103 clones.
Generally, the results indicated that the Toolik Lake microbial community differs more from the North Carolina lakes than the North Carolina lake communities differ from each other. The three Lake Townsend samples also showed variation as the samples differed with respect to the location and season of sampling. While the March and June collections at the same Lake Townsend location shared several OTUs with the other Lake Townsend and City lake samples, several multiple-copy OTUs were only found in the March collection, indicating that some microbial species thrive in the relatively cold waters of early Spring. Also, the two Lake Townsend samples collected on the same day showed the highest level of overall similarity. The library sampling method was able to detect similarities between samples, indicating that the microbial community is not too heterogeneous to analyze with molecular methods. In addition, the existence of unshared OTUs and the ability to detect quantitative differences between shared OTUs indicated differences between microbial communities that may be diagnostic of specific environmental conditions.
Based on the sequence information provided by the clones and information available in GenBank, two microarrays for testing water samples were made. The protocol for testing the microarray was as follows: appropriate prokaryotic and eukaryotic primers were used to amplify either 16S rDNA or 18S rDNA, respectively, from DNA that was extracted from the water samples as described above. The PCR products were then labeled by chemical attachment to either Cy3 (green) or Cy5 (red) dye, and upon denaturation, the labeled PCR products were hybridized to the array.
To make the arrays, 50-mer oligonucleotide sequences were spotted onto the surface of epoxy-coated glass slides. In Table 11, sequence identifications from Tables 2 and 3 are provided for each probe that was spotted to make the array shown in
TABLE 11
Prokaryotic (16S rDNA) probes
103P
103P
103P
103P
104P
105P
106P
107P
108P
109P
110P
103F1
103F1*
103F1*
Cy3
9mer
Eukaryotic (18S rDNA) probes
15P
15P
30P
31P
32P
16P
33P
34P
14P
35P
36P
38P
39P
40P
41P
37P
42F
42F**
Cy3
9mer
*reverse complementary sequence of 103F1;
**reverse complementary sequence of 42F
The experimental design is illustrated in
In the experiment shown in
The experiment illustrated in
The microarray is also capable of detecting known water pathogens and contaminants which affect water quality, thus raising the possibility of an “all in one” testing system. To test the feasibility of this additional feature, a microarray including 16S rDNA sequences from several cyanobacteria species was made. This microarray was tested with primers designed to amplify the rDNA of these species specifically, and the labeled products were hybridized to the microarray. As
TABLE 12
Oligonucleotide probes on array of FIG. 13
A
15P
30P
31P
32P
16P
33P
34P
14P
35P
36P
38P
39P
40P
41P
17P
29P
Cy3
9mer
B
10P
11P
12P
13P
19P
20P
21P
22P
18P
23P
24P
25P
26P
27P
28P
Cy3
9mer
C
51P
52P
53P
54P
55P
56P
57P
58P
60P
61P
62P
63P
Cy3
9mer
D
83P
81P
73P
74P
75P
76P
84P
85P
82P
80P
103P
104P
105P
106P
107P
108P
109P
110P
77P
78P
79P
Cy3
9mer
To generate the labeled probe for this experiment, Toolik Lake, AK and City Lake, NC genomic samples were amplified using cyanobacteria specific PCR primers in a multiplex format. Toolik Lake products were labeled with Cy3 (green) and City Lake products were labeled with Cy5 (red). The primer pairs were: Synechococcus. sp. LBP1, Synechococcus sp. LBG2, an unknown cyanobacteria clone LD27, and a degenerate Synechococcus primer set (Table 3). The four probes to cyanobacteria hybridized with amplicons from both lake samples as evidenced by the yellow signal in grid D (
Amplification of genomic sample DNA may be performed by multiplex PCR using primers chosen to provide products that can hybridize to taxon-specific DNAs. Using this protocol can dramatically reduce non-specific labeling, and eliminates the need for intermediate PCR reactions, which reduce sensitivity.
The arrays included nucleic acid sequences from variable regions of individual eukaryotic and prokaryotic rDNAs. Sequences spotted on the arrays included 32 probes derived from the literature that target known pathogens or contaminant microbes and 73 probes to sequences derived from freshwater environmental samples, including both known and novel sequences, and four cyanobacteria. The actual probe sequences spotted on the array shown in
TABLE 13
Primer/Probe combinations spotted on microarrays
GenBank
accession
GenBank
16S rDNA sequence
no.
18S rDNA sequence
accession no.
Enterococcus gallinarum, strain LMG 13129
AJ301833
Cryptosporidium parvum
AF222998
Burkholderia cepacia
AB091761
Acanthamoeba mauritaniensis
AY351647
Burkholderia cepacia genomovar III
AF148556
Cyclospora cayetanensis
AF111183
Uncultured human fecal bacterium HF74
AF233412
Entamoeba histolytica
X65163
Uncultured human fecal bacterium HF8
AF233408
Giardia intestinalis isolate
AF199449
Uncultured human fecal bacterium HF10
AF233413
Isospora belli
AF106935
Bacillus anthracis strain S51
AB116124
Microsporidium sp. STF
AY140647
Clostridium botulinum strain AIP 355.02
AY303799
Naegleria fowleri
AF338423
Francisella tularensis strain 3523
AY243028
OTU TL1A1, multi-copy, unidentified
Yersinia pestis
AF366383
OTU TL1A2, multi-copy, unidentified
Brucella melitensis
AF220149
OTU TL1A9, multi-copy, unidentified
Burkholderia mallei strain 2000031063
AY305760
OTU TL1A12, multi-copy, unidentified
Chlamydophila psittaci clone cvCps2
AY334530
OTU TL1A16, multi-copy, unidentified
Coxiella burnetii, strain Nine Mile
Y11502
OTU TL1A21, multi-copy, unidentified
Escherichia coli O157:H7
AB035920
OTU CL1A3, single-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A4, single-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A5, single-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A6, single-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A8, multi-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU LT2A12, multi-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU LT2A20, single-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU LT1A3, single-copy, unidentified
Escherichia coli O157:H7 EDL933
NC 002655
OTU LT1A42, multi-copy, identified
as Cryptomonas sp., strain M420
Escherichia coli K12
NC 000913
OTU LT1A5, multi-copy, unidentified
Escherichia coli K12
NC 000913
OTU LT1A4, multi-copy, identified
as Cryptomonas ovata,
strain CCAP 979/61
Escherichia coli K12
NC 000913
OTU LT1A8, multi-copy, unidentified
Escherichia coli K12
NC 000913
OTU LT2A7, multi-copy, identified
as Dileptus sp.
Rickettsia prowazekii
M21789
OTU LT1A9, single-copy, unidentified
Salmonella typhimurium
Z49264
OTU LT2A19, single-copy, identified
as Coleps sp.
Vibrio cholerae (CECT 514 T)
X76337
OTU LT1A10, multi-copy, unidentified
Campylobacter jejuni strain B99/206
AF550630
OTU LT1A11, single-copy, unidentified
Legionella pneumophila serogroup 6
AJ496383
OTU LT1A13, single-copy, unidentified
Leptospira interrogans
Z12817
OTU LT3A2, single-copy, unidentified
Pseudomonas aeruginosa, strain WatG
AB117953
OTU LT3A5, multi-copy, unidentified
OTU TL1A1, multi-copy, unidentified
OTU LT3A6, multi-copy, unidentified
OTU TL1A2, multi-copy, unidentified
OTU LT3A11, single-copy, unidentified
OTU TL1A6, single-copy, unidentified
OTU LT3A13, single-copy, unidentified
OTU TL1A7, multi-copy, identified as
OTU LT1A1, multi-copy, unidentified
Uncultured beta proteobacterium clone OS1L-16
OTU LT1A31, multi-copy, identified as
OTU LT1A38, multi-copy, unidentified
Uncultured Crater Lake bacterium CL500-18
OTU LT1A55, multi-copy, identified as
Uncultured freshwater bacterium LCK-26
OTU CL1A2, multi-copy, unidentified
OTU CL1A9, multi-copy, identified as
Zoogloea ramigera
OTU CL1A10, multi-copy, unidentified
OTU CL1A15, single-copy, identified as
Uncultured Crater Lake bacterium CL0-27
OTU LT1A54, multi-copy, identified as
Uncultured Crater Lake bacterium CL0-64
OTU LT1A27, multi-copy, identified as
Uncultured actinomycete clone SFD1-39
OTU LT2A3, multi-copy, unidentified
OTU LT1A46, multi-copy, identified as
Uncultured planctomycete clone
CY0ARA031E04
OTU LT2A12, multi-copy, unidentified
OTU LT2A16, multi-copy, unidentified
OTU LT1A53-3A9, multi-copy, identified as
Synechococcus sp.
OTU LT1A53, multi-copy, identified as
Synechococcus sp. LBG2
OTU LT3A9, multi-copy, identified as
Synechococcus sp. LBP1
OTU LT3A11, multi-copy, identified as
Unidentified cyanobacterium clone LD27
Arsenite-oxidizing bacterium MLHE-1
Thiomicrospira sp. CVO
Desulfovibrio longreachii
Bacillus arsenicoselenatis
OTU LT3A1, single-copy, unidentified
OTU LT3A2, multi-copy, unidentified
OTU LT3A7, multi-copy, unidentified
OTU LT1A15, single-copy, unidentified
OTU LT1A16, multi-copy, unidentified
OTU LT1A18, multi-copy, unidentified
OTU LT1A35, multi-copy, unidentified
OTU LT1A55, multi-copy, unidentified
TABLE 14
Oligonucleotide probes on array of FIG. 14
A
B
19P
20P
21P
22P
18P
23P
24P
25P
26P
27P
28P
17P
29P
Cy3
9mer
C
D
43P
44P
45P
46P
47P
48P
95P
96P
97P
86P
87P
88P
49P
50P
65P
66P
67P
68P
91P
98P
92P
99P
89P
90P
69P
70P
71P
72P
93P
100P
94P
101P
102P
Cy3
9mer
E
F
15P
30P
31P
32P
16P
33P
10P
11P
12P
13P
1P
2P
34P
14P
35P
36P
38P
39P
3P
4P
5P
6P
7P
8P
40P
41P
Cy3
9mer
G
H
51P
52P
53P
54P
55P
56P
83P
81P
73P
74P
75P
76P
57P
58P
60P
61P
62P
63P
84P
85P
82P
80P
77P
78P
79P
106P
107P
108P
103P
104P
105P
109P
110P
Cy3
9mer
Such taxon-specific arrays may be developed for specific bodies of water. For example, arrays may be developed for lakes, marshes, tidal pools, or estuaries. Such arrays may include probes developed for freshwater systems, as these may be diagnostic for known pathogens (e.g., coliform bacteria) or environmental conditions (e.g., eutrophication). Also, sequences specific to microbes known to be common in the body of water of interest may be used. For example, for estuaries, phytoplankton populations have been described (Williams, R. B. and M. B. Murdoch 1966, Limnology and Oceanography 11:73–82., Thayer, G. W., 1971 Estuaries 12:240–253; Mallin 1994, Mallin, et al. 2000). A review of the literature indicates that many of the sequences that may be used are known (Table 15). Using this information, primers and probes to these common organisms, may be designed. Finally, probes for the array may be derived by sequencing clonal libraries derived from field samples as described herein for the lake samples to develop additional OTUs. For example, to develop an estuary array, water samples may be collected every few months in estuarine tidal creeks at various sites representing a range of estuarine conditions. Specific sampling locations may be water quality monitoring stations, and samples may be taken late on the flooding tide and six hours later on the ebbing tide, to provide a representative sample of both the community that enters the estuarine site as well as the community that leaves the estuarine site with the falling tide.
It should be understood that various changes and modifications to the embodiments described herein will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present invention and without diminishing its attendant scope and/or advantages.
TABLE 15
Examples of organisms of interest for North Carolina
estuarine microarray targets based on literature reports4
Phytoplankton
Cyclotella spp.
Melosira spp.
Nitzschia spp.
Navicula spp.
Psuedo-nitzschia australis3
Skeletonema costatum1
Thalassiosira spp.
Amphidinium spp.
Ceratium spp.
Chattonella spp.3 (C. antiqua,
Gymnodinium sanguineum
C. verruculosa)
Heterocapsa triquetra1
Heterosgima akashiwo3
Hematodinium perezi3
Karenia brevis3
Karlodinium micrum1
Katodinium rotundatum1
Pfiesteria piscicida3, P. shumwayae3
Prorocentrum minimum1
Calicomonas ovalis
Chlamydomonas spp.
Chroomonas spp. (C. minuta,
Cyrptomonas testaceae
C. amphioxiae)
Hemiselmis virescens
Phaeocystis globosa
Pyramimonas
Eutreptia1
Bacteria
Acinetobcter spp.
Alcaligenes spp.
Bacteroides spp.2
Enterococcus spp.2
(E. faecalis, E. faecium)
Escherichia spp.2,3 (E. coli,
Flavobacterium spp.
E. coli O157H7)
Oceanospirillum spp.
Salmonella spp.2,3 (S. typhi,
S. non-typhi)
Psuedomonas aeruginosa
Shigella sp.2,3
Clostridium sp.2,3 (C. perfringens,
C. botulinum Type E)
Vibrio sp.3 (V. anguillarum,
V. cholerae 01, V. cholerae non 01,
V. parahaemolyticus V. vulnificus
Virus
Hepatitis A3
Norwalk virus3
Adenovirus3
rotavirus3
Protozoa
Kudoa spp.3
Cryptosporidium spp.2,3
(K. clupeidae, K. fundulae)
Giardia2,3
Perkinsus marinus3
Haplosporidium3
Fungi
Aphanomyces invadens3
1Genera or species referenced in the literature as commonly found in southeastern estuarine systems, and likely to be indicators of good ecosystem health (e.g. Campbell, 1973, Univ. of N.C. Sea Grant Publication, UNC-SG-73-07; Mallin, et al. 2000, American Scientist, 88:26–37; Shubert, 1984, In Algae as Ecological Markers, Academic Press, NY, p. 434; Stoermer and Smol, 1999, In The Diatoms: Applications For the Environmental and Earth Sciences, Cambridge Univ. Press, Cambridge, UK, page 469; Thayer, 1971, Estuaries, 12:240–253, Williams and Murdoch, 1966, Limnology and Oceanography, 11:73–82;).
2Microbes linked to specific contamination sources (e.g. human sewage) which indicate point or non-point source pollution (e.g. Bernhard and Field, 2000, Applied and Environmental Microbiology, 66:4641–4648; Lipp, et al. 2001, Marine Pollution Bull., 42:286–293; Mallin, et al., 2000b, Ecological Applications, 10:1047–1056' USEPA, 1985, Test methods for Escherichia coli and Enterococci in water by the membrane filter procedure, EPA600/4-85/076)
3Known human, fish, or shellfish pathogens or parasites (e.g. DeLeon, et al. 1990, In Proceeding of the Water Quality Conference, San Diego, CA, American Water Works Association, 18:833–853; Grimes 1991, Estuaries, 14:345–360; Kane, et al., 1998, Maryland Medical Journal, 37:106–112; Lipp, 1999, , Reed and Francis-Floyd, 1996, Vibrio Infections of Fish, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida web-site; Shields, 1997, An investigation into the epidemiology of Hematodinium perezi, a parasitic dinoflagellate in the blue crab, Callinectes sapidus, available on-line)
4Many of the taxa listed have GenBank sequence entries for one or more species.
Rublee, Parke A., Henrich, III, Vincent C.
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